U.S. patent application number 08/879471 was filed with the patent office on 2001-10-04 for systems and methods for identifying images.
This patent application is currently assigned to LAU TECHNOLOGIES. Invention is credited to SLOCUM, LEE G., WEIDER, YONA.
Application Number | 20010026631 08/879471 |
Document ID | / |
Family ID | 23616605 |
Filed Date | 2001-10-04 |
United States Patent
Application |
20010026631 |
Kind Code |
A1 |
SLOCUM, LEE G. ; et
al. |
October 4, 2001 |
SYSTEMS AND METHODS FOR IDENTIFYING IMAGES
Abstract
Systems and methods are disclosed that employ facial recognition
to create, maintain and use databases that store data records of
individuals. In particular, systems and methods are disclosed that
employ facial recognition to control the production of
identification cards that include an image of a person's face and
demographic data. Preferrably, the systems and methods include
lensing modules adapted for efficiently identifying within a
picture image the location of a person's face.
Inventors: |
SLOCUM, LEE G.;
(WILLIAMSBURG, NH) ; WEIDER, YONA; (NEWTON,
MA) |
Correspondence
Address: |
LAHIVE AND COCKFIELD,LLP
28 STATE STREET
BOSTON
MA
02109
|
Assignee: |
LAU TECHNOLOGIES
|
Family ID: |
23616605 |
Appl. No.: |
08/879471 |
Filed: |
June 20, 1997 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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08879471 |
Jun 20, 1997 |
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08408517 |
Mar 20, 1995 |
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Current U.S.
Class: |
382/115 |
Current CPC
Class: |
A61B 5/1176 20130101;
G07C 9/253 20200101; G06V 40/16 20220101 |
Class at
Publication: |
382/115 |
International
Class: |
G06K 009/00 |
Claims
We claim:
1. Apparatus for manufacturing an identification card, comprising
an image acquisition element for generating a picture signal that
includes an image that is representative of a person's face, a
vector memory having storage for plural eigenvector signals each
one of which represents an eigenvector of a multi-dimensional image
space, means for generating a projection signal representative of a
portion of said picture signal encoded as a weighted function of
said plural eigenvector signals, an image database memory having
storage for projection signals each composition signal being
representative of a weighted set of said eigenvector signals and
each being associated with an image of a specific person's face, a
demographic database memory having storage for one or more data
records wherein each said data record is associated with a
respective one of said projection signals and includes an
identification signal for identifying said data record, recognition
means for determining whether said projection signal is
substantially representative of one or more of said stored
projection signals and for generating a match signal responsive to
a detected match between said projection signal and one of said
stored projection signals, enforcement means responsive to said
match signal, for selecting one or more of said data records, and a
printer element arranged for recording information representative
of said picture signal and said selected identification signal onto
a blank data card to generate said identification card.
2. Apparatus according to claim 1 wherein said means for generating
a projection signal includes a locator module having prefilter
means adapted to identify portions of said picture signal possibly
representing said image of a person's face, means for encoding each
identified picture portion as a weighted function of said plural
eigenvector signals, and selector means for selecting one of said
identified picture portions as a function of said projection
signals.
3. Apparatus according to claim 1 wherein said enforcement means
comprises an image server element adapted for storing picture
signals associated with respective ones of said data records, and a
monitor element coupled to said image server element and said
recognition means and being adapted to display picture signals as a
function of said match signal.
4. Apparatus according to claim 1 wherein said enforcement means
couples to said printer element for selectively and controllably
recording information in response to said match signal.
5. Apparatus according to claim 3 wherein said monitor element
includes a printer element for generating a recorded signal
representative of one or more picture signals.
6. Apparatus according to claim 1 further including a network job
builder element adapted for generating, in response to said match
signal, a batch signal representative of information to be recorded
on to one or more identification cards.
7. Apparatus according to claim 1 further including registration
means for generating a data record associated with said picture
signal and for generating one of said identification signals for
identifying said data record.
8. Apparatus according to claim 1 further including selection means
for selecting a portion of said picture signal representative of
select characteristics of a person's face.
9. Apparatus according to claim 8 wherein said selection means
includes means for selecting a portion of a picture signal
representative of an eye.
10. Apparatus according to claim 1 further including means for
normalizing said picture signal according to preselected user
criterion.
11. Apparatus according to claim 10 wherein said means for
normalizing includes means for selectively adjusting a grey-scale
parameter of said picture signal.
12. Apparatus according to claim 10 wherein said means for
normalizing includes means for selectively adjusting an inclination
parameter of said picture signal.
13. Apparatus according to claim 10 wherein said means for
normalizing includes means for scaling said picture signal.
14. Apparatus according to claim 1 wherein said image acquisition
element includes a video camera element.
15. Apparatus according to claim 1 wherein said image acquisition
element includes a photographic camera element and a scanner
element.
16. Apparatus according to claim 1 wherein said recognition means
includes text query means coupled to said demographic database
memory element for comparing signals representative of textual
information with said identification signals stored in said data
records.
17. Apparatus for sorting a database of picture signals, comprising
a picture memory adapted for storing picture signals, a reference
memory having storage for plural eigenvector signals each one of
which represents an eigenvector of a multi-dimensional image space
and having storage for a subspace signal representative of a
subspace defined by said plural eigenvector signals, means for
selecting a picture signal from said picture memory and for
generating a projection signal representative of a portion of said
picture signal encoded as a weighted function of said plural
eigenvector signals, means for computing a distance signal that
represents the distance between a point defined by said projection
signal and said space defined by said subspace signal,
classification means for determining as a function of said distance
signal whether a picture signal is representative of an image of a
person, and sorting means for sorting picture signals according to
whether said picture signal is representative of a person.
18. Apparatus according to claim 17 wherein said means for
generating a projection signal includes prefilter means adapted to
identify portions of said picture signal possibly representing an
image of a person's face, means for encoding each identified
picture portion as a weighted function of said plural eigenvector
signals, and selector means for selecting one of said identified
picture portions as a function of said projection signals.
19. Apparatus according to claim 17 further including means for
deleting a picture signal from said picture memory as a function of
said distance signal.
20. Apparatus according to claim 17 further including a demographic
database memory having storage for one or more data records wherein
each said data record is associated with a respective one of said
picture signals and includes an identification signal for
identifying said data record, and means for deleting a data record
as a function of said distance signal.
21. Apparatus according to claim 17 further including list means
for generating as a function of said distance signal a list signal
representative of one or more picture signals.
22. Apparatus according to claim 17 wherein said means for
computing said distance signal includes a threshold memory for
storing a threshold signal representative of a preselected
threshold, and comparison means for comparing said distance signal
with said threshold signal.
23. Apparatus according to claim 17 wherein said means for
computing said distance signal includes selection means for
selecting a portion of a picture signal representative of a select
characteristic of a person's face.
24. Apparatus according to claim 17 wherein said selection means
includes means for selecting a portion of a picture signal
representative of a person's eye.
25. Apparatus for searching a picture signal to locate an image
representative of a face, comprising a picture memory for storing
said picture signal, a vector memory having storage for plural
eigenvector signals each one of which represents an eigenvector of
a multi-dimensional image space, a locator module that includes
prefilter means, coupled to said picture memory and adapted to
identify portions of said picture signal possibly representing an
image of a face, projection means for generating a projection
signal by encoding each identified picture portion as a weighted
function of said plural eigenvector signals, and selector means for
selecting one of said identified picture portions as a function of
said projection signals.
26. Apparatus according to claim 25 wherein said prefilter means
includes means for measuring a grey-scale characteristic of a
picture portion and means for comparing said measured grey-scale
value with a user-determined grey-scale value that indicates the
absence of an image of a face.
27. Apparatus according to claim 25 wherein said prefilter means
selects portions of said picture signal wherein each portion is
spaced apart from the next portion and wherein the distance between
portions is selected as a function of said measured grey-scale
characteristics.
28. Apparatus according to claim 25 wherein said locator module
further includes scaling means for adjusting the relative
dimensions of said picture signal as a function of said projection
signal.
29. Apparatus for normalizing images representative of a person's
face, comprising a picture memory adapted for storing one or more
picture signals each having an image representative of a person's
face, a vector memory having storage for plural eigenvector signals
each one of which represents an eigenvector of a multi-dimensional
image space, means for selecting one of said picture signals and
for generating a projection signal representative of a portion of
said selected picture signal encoded as a weighted function of said
plural eigenvector signals, means for generating a distance signal
representative of a distance between a point defined by said
projection signal and a subspace of said multi-dimensional image
space, and normalizing means for adjusting a characteristic of said
selected picture signal as a function of said distance signal.
Description
FIELD OF THE INVENTION
[0001] The field of the invention relates to systems and methods
for data processing and more particularly to systems and methods
that employ facial recognition to manage databases containing
images of individuals.
BACKGROUND OF THE INVENTION
[0002] Computerized databases can be adapted to store many
different kinds of data, including sounds, images and text. This
flexibility allows database designers to construct databases that
have data records that organize and store information in several
different formats, such as text and sound and thereby to provide
database systems that are more particularly suited to the
application at hand.
[0003] In one common example, government agencies and businesses
use computer databases to store information about select
individuals into data records that include demographic data stored
as text information and a picture of the individual stored as a
digitally encoded image. Therefore, a State Department of Motor
Vehicles, can create a database of registered drivers that includes
a data record for each registered driver. Each data record can
store text information, such as the driver's name and address, and
image information, such as a digitally encoded picture of the
driver. The Department of Motor Vehicles can maintain this record,
and continually update the contents as the driver's history and
data change.
[0004] Although computer databases provide an efficient way to
store image and text data, they generally fail to provide any way
to search or sort the image information stored therein. This
inability is particularly burdensome if the image information is
the most reliable or complete information in the data record.
[0005] Moreover, this inability prevents an operator from
automatically searching through the database to find a particular
image of a person. Accordingly, to search the images in a database,
the operator must call up each data record and view that record's
stored image. This is such a time consuming and labor intensive
process, that image searches of large databases is practically
impossible. Consequently, there is little to prevent a person from
registering multiple times with an agency, such as the Registry of
Motor Vehicles, or a State Welfare Department, by providing
fraudulent demographic data during each registration.
[0006] Moreover, the quality and characteristics of the images
stored in the database can vary widely. For example, the grey scale
of any two images can be markedly different. These variations make
it more difficult for an operator to compare stored images.
[0007] Therefore it is an object of the present invention to
provide improved systems and methods for maintaining databases that
store image information as part of a data record.
[0008] It is a further object of the present invention to provide
systems and methods that can efficiently employ image information
to control the entry of data into a database.
[0009] It is yet another object of the invention to provide
improved systems and methods for storing image information in a
normalized format within a database.
[0010] These and other objects of the present invention will become
apparent by following the description of certain embodiments of the
present invention.
SUMMARY OF THE INVENTION
[0011] The present invention provides systems and methods that
employ facial recognition to create, maintain and use databases
that store data records of individuals. In particular, the present
invention provides systems and methods that are adapted to employ
select facial recognition techniques to analyze a picture of a
person's face. These select facial recognition techniques generate
a set of values, hereinafter referred to as a "projection signal",
that, as a set, are descriptive of the analyzed picture image and
provide for highly compact storage of the critical identity
characteristics of a person's face. The generated projection signal
can be stored as a data field in a data record that is associated
with the individual depicted in the picture. This data record can
also include demographic data fields for organizing information,
such as address information, social security numbers, and other
identifying information with the image information. The invention
provides systems and methods that are adapted to work with data
records that include data fields of descriptive image information,
and to provide systems that can search, compare and sort data
records according to image information recorded therein.
[0012] To this end, systems and methods are described for creating
and employing databases that have data records which contain image
information of a person's face. These database systems and methods
are adapted for efficiently storing, sorting, and comparing data
records as a function of the image of a person's face.
[0013] In one embodiment of the invention, systems are provided for
manufacturing identification cards, such as driver's licenses,
military identification cards, welfare identification cards, pistol
permits and other photo-identification cards. The systems are
adapted for performing a select principal component analysis facial
recognition technique. The facial recognition technique employed by
the present invention allows, in one use, the systems to police the
manufacture of identification cards to eliminate issuing multiple
cards under different names to a single applicant.
[0014] These systems generally include an image acquisition
element, such as a video camera or a photographic camera and a
scanner, that generates a digitized picture of the applicant's
face. A vector memory stores a plurality of eigenvectors defining a
multi-dimensional image space. A data processor, such as a
conventional workstation, is configured to project the digitized
picture onto the multi-dimensional image space, to encode the
picture as a weighted function of the plural eigenvectors. An image
database couples to the data processor to provide storage for a
database of known projection signals each being representative of a
weighted set of the eigenvectors associated with an image of a
specific person's face. A demographic database stores a number of
data records wherein each data record is associated with a
respective one of the stored projection signals and the individual
whose image is represented thereby. Each data record also includes
an identification signal for identifying that particular data
record.
[0015] Typically, the data processor includes a recognition program
element that is adapted for recognizing a person. Generally, the
recognition program element compares the generated projection
signal against the projection signals stored in the system. As the
projection signals represent the image of a person's face, similar
projection signals are likely to represent the same person or a
person with a similar appearance. Therefore, the program element is
adapted to determine whether the generated projection signal is
substantially representative of one or more of the stored
projection signals and to indicate if a match is detected.
[0016] In a further embodiment, the recognition program element
includes a text query element for comparing text information with
the identification signals stored in the data records. The text
query element compares, sorts and orders data records as a function
of text signals, such as demographic data, stored in the data
records. In an optional configuration, the recognition program
element employs the text query element to identify a subset of data
records as a function of select demographic data. In a subsequent
operation, the recognition program element operates on the subset
of data records to determine whether the generated projection
signal is substantially representative of one of the stored
projection signals.
[0017] In a preferred embodiment of the present invention, these
systems include a location device that searches through the
acquired picture to identify a portion of the picture that contains
an image of a person's face. For example, in a picture that depicts
a person standing in front of a wall in a police line up, the
location device will ignore the background wall and other clutter
and will identify that portion of the picture that contains the
image of the person's face. In one embodiment, the location device
has a prefilter element that makes a preliminary examination of one
portion of the picture to determine if that portion of the picture
is likely to contain the image of a person's face. One type of
prefilter element has a grey-scale variance detector that
determines how much variance exists between the grey-scale of the
selected picture portion, and the typical grey-scale of a picture
portion that contains a face. This computationally efficient
calculation allows the prefilter element to distinguish quickly
between a portion of the picture that depicts a wall or a screen
positioned behind the person, and a portion of the picture that
contains the image of the person's face.
[0018] Preferably the recognition program element also includes a
normalizing element that adjusts the acquired picture according to
preselected user criterion. The normalizing element typically
includes an element for selectively adjusting a grey-scale
parameter of the acquired picture, and an element for selectively
adjusting an inclination or tilt parameter of the picture. This
normalization element helps minimize problems during the
recognition process which are caused by variations in conditions,
such as lighting, during image acquisition.
[0019] In one embodiment, an enforcement mechanism monitors the
recognition program and notes if any matches occur between the
generated projection signal and the stored projection signals. The
enforcement mechanism notes each favorable comparison and makes a
list of every data record that appears to contain an image of the
person applying for an identification card. The enforcement
mechanism may further include an image server element that is
adapted for storing pictures associated with respective ones of
said data records. A monitor coupled to the image server displays
the pictures of those people that have similar image characteristic
as the applicants. An operator can detect if the Applicant is
attempting to register into the database under a different
name.
[0020] In another option, a printer element can connect to the
system and record information representative of the picture signal
and the identification signal onto a blank data card to generate an
identification card. In one embodiment, the enforcement mechanism
couples to the printer and prevents the printer from printing an
identification card for any data record associated with a picture
that is substantially similar to the picture of the applicant.
[0021] In a further embodiment of the present invention, the
identification card manufacturing system also includes a selection
element that selects a portion of the picture that represents a
select characteristic of the applicant's face. In one example, the
selection element selects the portion of the picture that
represents the applicant's eyes. By analyzing one portion of a
person's face, the system can recognize a person that is wearing a
disguise, such as a beard or wig. In this example, the system
projects the portion of the picture that includes the image of the
person's eyes onto the multi-dimensional space, and generates a set
of values that are descriptive of this portion of the picture. The
recognition program element compares the generated values against
values stored in the database and identifies data records having
images similar to the applicant's image.
[0022] In another embodiment of the present invention, systems are
provided for sorting pictures stored with data records. In
particular, systems are described that sort pictures as a function
of the class of object, such as whether the image can be classified
as a face, an eye, or a mouth. These sorting systems are adapted
for sorting through a database of pictures to identify those
pictures that represent a select class of objects. In one
particular example, the sorting system is adapted to sort through a
database of pictures to identify those pictures that represent the
face of a person. The system can then make a list of the data
records that fail to contain an image of a face, and a system
operator can examine these records to identify those records that
are to be deleted from the system.
[0023] Generally these systems include a picture memory adapted for
storing picture signals, a reference memory having storage for the
plural eigenvectors of a multi-dimensional image space and having
storage for a subspace signal representative of a subspace defined
by the plural eigenvectors, a selection element for selecting a
picture signal from the picture memory and for generating a
projection signal representative of the picture signal encoded as a
weighted function of the plural eigenvector signals, a computing
element for computing a distance signal that represents the
distance between a point defined by the projection signal and the
space defined by the subspace signal, and a classification element
for determining as a function of the distance signal whether a
picture signal is representative of an image of a person. This
system therefore provides a mechanism to search through a database
of images and identify those data records that contain image data
of a particular class of objects, such as faces.
[0024] In one embodiment, these systems include an element for
deleting automatically a picture signal from the picture memory as
a function of the distance signal. Optionally, the system includes
a demographic database memory for storing data records, and an
element for deleting a data record from the demographic database as
a function of the generated distance signal.
[0025] The invention will now be explained with reference to
certain illustrated embodiments to provide greater detail of the
structure and operation of the systems and methods that can be
realized by the present invention.
BRIEF DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS
[0026] FIG. 1 illustrates a system for manufacturing identification
cards which includes a data acquisition element that employs facial
recognition to control data records entered into a database;
[0027] FIG. 2 is a flow chart diagram of a process for verifying
information stored in a data record; and
[0028] FIG. 3 illustrates a flow chart diagram of a process
practicable with the system depicted in FIG. 1, and adapted for
finding within a picture an image representative of a face.
DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS
[0029] FIG. 1 illustrates a system 10 for manufacturing
identification cards, such as driver's licenses, welfare cards,
firearm identification cards, military identification cards and
other identification cards that typically reproduce in a printed
format demographic data and an image of an individual. The image
and demographic data recorded onto an identification card is
generally reliable, as identification cards typically include
seals, signatures and other devices that make forgeries difficult
to produce. Accordingly, businesses and government agencies
commonly provide identification cards to those individuals that are
registered, into an official record maintained by the agency.
Typically, these official records are maintained in a computer
database that includes a data record, or file, for each registered
individual. The system 10 illustrated in FIG. 1 is adapted to
control such an official record by controlling the data entered
into the official record and by accessing information in these
records to manufacture identification cards.
[0030] To this end, the system 10 is adapted to analyze data
records being stored in a database of official records and to
control the manufacture of identification cards that represent in
recorded form, information from a data portion of an official
record. The system 10 includes a vision inspection cell 12, a
recording unit 14, a packaging unit 16, a network job builder unit
18, a central image server 20, a data acquisition unit 22, and a
demographic database memory 24. System 10 illustrated in FIG. 1 is
one system constructed according to the invention, that employs
facial recognition techniques to manage and control a database
containing image information that includes at least in part, images
representative of a person's face. In particular, the system 10
employs facial recognition technology to prevent a single
individual from acquiring multiple identification cards, such a
drivers licenses, under different names. Additionally, the system
10 can sort a database of images to remove from the database those
data records that contain insufficient or incorrect image
information, and can process and adjust image information to
generate an image signal suitable for printing on an identification
card.
[0031] The illustrated system 10 includes a recording unit 14,
vision inspection cell 12 and packaging unit 16 that generate and
inspect identification cards. Such units are described in U.S.
patent application Ser. No. 08/316,041, entitled "Systems and
Methods for Recording Data", filed Sep. 30, 1994, assigned to the
Assignee hereof, and incorporated herein by reference. The data
acquisition element 22 acquires information necessary to generate
an identification card. The data acquisition element 22 can examine
and process an acquired image to detect if this image is
substantially similar to an image already recorded into the
database. Additionally, the data acquisition element 22 can process
the required image to determine if it is likely to represent the
image of a person's face. Once the information is analyzed, the
data acquisition element 22 determines if the acquired information
is to be entered as a data record in the official register
database. The data acquisition element 22 transmits acquired images
to the control image server 20 data memory. The central image
server 20 data memory acts as a depository for images collected by
the data acquisition element 22. Optionally, the system 10 includes
a separate database memory, such as the database memory 36, which
stores the images acquired by the data acquisition element 22.
[0032] The central image server 20 can access demographic data from
the demographic database 24 and send image and demographic
information to the network job builder unit 18. The network job
builder unit 18 collects the image and demographic data together
and issues a command to the recording unit 14, that requests the
recording unit 14 to record information onto a datacard 40. The
recorded information includes the image acquired by the data
acquisition element 22 and demographic data acquired from the
demographic database memory 24. The recording unit 14 passes the
recorded data card to the vision inspection cell 12. The vision
inspection cell 12 inspects the information recorded onto the
datacard 40 to determine if the recorded datacard meets certain
user selected criteria. The inspection cell 12 passes the inspected
datacard to the optional packaging unit 16.
[0033] The packaging unit 16 receives a signal from the vision
inspection cell 12 that indicates whether or not the recorded
datacard 40 has been successfully manufactured. If the card has
been successfully manufactured, the packaging unit 16 places the
recorded datacard 40 into a carrier element, such as an envelope,
and prepares the envelope for distribution, typically by mail.
Alternatively, if the vision inspection cell 12 indicates that the
recorded datacard 40 fails to meet user selected criteria, the
packaging unit 16 places the recorded datacard 40 into a disposal
bin.
[0034] With reference again to FIG. 1, the data acquisition element
22 can be described in more detail. The illustrated data
acquisition element 22 is a programmable hardware device that
includes an image acquisition element 30, a monitor 32, a data
processor 34, a keyboard 34A, and an optional image database memory
36. As further illustrated by FIG. 1, the data processor 34
connects via transmission paths to the image database memory 36 and
to the central image server 20. The data processor 34 further
connects via a transmission path to the image acquisition element
30, that is depicted in FIG. 1 as a camera, such as a video camera
that acquires images and generates standard video signals
representative of the acquired images. The illustrated data
processor 34 is a conventional computing system, such as a SUN
SPARK workstation, that includes a video interface card for
interfacing with the camera acquisition element 30. The data
processor 34 further includes a program element, i.e., an
application program, that controls these elements to acquire,
process and store both image and text information.
[0035] The image acquisition element 30 which can be a camera, such
as a video camera, that captures image data that is representable
by pixel data. The depicted image acquisition element 30 is a video
camera that produces an analog video signal that encodes an image
as pixel data. The video signal can be formatted into any of the
conventional video formats, including RS-170/CCIR or any
proprietary video format. The analog signal is received by a camera
interface in the data processor 34. Alternatively, the image
acquisition element can be a digital camera that generates image
information in a digital format. Other image acquisition elements
can be practiced with the present invention without departing from
the scope thereof.
[0036] In an alternative embodiment, the image acquisition element
30 is a scanner element that is adapted for scanning photographic
film pictures into a computer memory. One such scanner is the
AVR3000 manufactured by AVR Technology of San Jose, Calif. The
scanner element image acquisition unit encodes the photographic
film picture into pixel data and transmits the pixel data to the
data processor 34 to thereby provide the data processor 34 with a
machine readable representation of a picture. Other image
acquisition elements suitable for representing an image or picture
in machine readable form are practicable with the invention without
departing from the scope of thereof.
[0037] The illustrated optional monitor 22 is a conventional video
display monitor such as the type commonly employed for displaying
video images including text, graphics, and images. As will be
explained in greater detail hereinafter, the data processor 34, in
one embodiment, operates the video monitor 32 to display picture
signals representative of images of individuals which are
maintained as image files within the image database 36.
[0038] The database memory element 36 stores data records, or
electrical signals representative of data records, wherein each
data record is associated with an individual that has been
registered into the database. The database memory 36 can be any
conventional addressable computer memory adapted for storing
electrical signals representative of data, and can include
electrical circuit card assemblies adapted for storing information
and/or controlling data storage devices, such as optical storage
disks, hard disks, and tape drives. The database stored in memory
element 36 can be a database of all registered drivers within a
certain state, all individuals registered into a state welfare
program, all individuals in a state that have been issued firearm
identification cards, and so forth. Each data record stored within
the memory element 36 can be employed by the system 10 to generate
an identification card. The identification card can be issued to a
qualified individual to verify that particular individual has been
validly registered with an authorized agency or entity and has been
granted the privileges identified by the issued identification
card. As can be seen from this description, it is a function of the
system 10 to maintain the integrity of the database stored in the
database memory 36. In particular, it is a function of the system
10 to prevent an individual from fraudulently obtaining one or more
identification cards under different names.
[0039] The illustrated demographic database memory 24 is a
conventional computer memory of the type commonly used for storing
data, or electrical signals representative of data, for use by a
data processing unit such as the data processing unit 34. The
demographic database memory 24 stores data records representative
of individuals whom have been registered by an agency into an
official record. Accordingly, the database stored in the
demographic database memory 24 represents the official record of
those individuals that are officially registered as authorized
users, members, or participants in a program or other organization
administered by an agency such as a business or government
agency.
[0040] The data processor 34 depicted in FIG. 1, is a data
processor having a processing unit, data memory, and program
memory. Additionally, the depicted data processor 34 includes a
video interface card of the type suitable for interfacing with a
camera element that generates electrical signals representative of
video images. In one embodiment, the data processor 34 is a SUN
workstation, however it should be apparent to one of ordinary skill
in the art that other data processor systems are employable with
the present invention without departing from the scope thereof. The
data processor 34 includes a data record verification module that
analyzes information acquired by the data acquisition element 22
and determines if the acquired information is to be entered as a
data record into the official record maintained within the
demographic database 24. In a preferred embodiment of this
invention, the verification module is implemented as a program
element stored in the program memory of the data processor 34,
however it should be apparent to one of ordinary skill in the art
of electrical engineering that the verification module can also be
implemented as an electrical circuit card assembly.
[0041] FIG. 2 illustrates a flow chart diagram of a process 100
performed by the verification module. The process 100 employs image
information acquired by the acquisition element 30 and text
information entered at the keyboard element 34A to verify each data
record being entered into the official database stored in the
database memory 24. The process 100 begins at step 110 when the
data acquisition element 22 has acquired sufficient information to
generate a data record. For example, the data acquisition element
22 depicted in FIG. 1 collects information for a data record that
includes an image of an applicant for a driver's license and the
necessary descriptive demographic information. In step 120 the
process 110 encodes the image information acquired by the image
acquisition element 30. The encoding process includes an
eigenvector projection technique that encodes an image of a
person's face as a weighted set of eigenvectors.
[0042] This eigenvector projection technique is described more
fully in U.S. Pat. No. 5,164,992, entitled "Face Recognition
System", issued to Turk et al., and incorporated by reference
herein. As described therein, an image of a face is projected onto
a space defined by a set of reference eigenvectors. The reference
set of eigenvectors, or eigenfaces, can be thought of as a set of
features which together characterize the variation between face
images within a reference set of face images. This distribution of
faces in the reference set of faces can be characterized by using
principal component analysis. The resulting eigenvectors define the
variation between the face images within the reference set of
faces, and can be referred to as eigenfaces.
[0043] In one embodiment of the invention, a training reference set
of faces is produced by acquiring a number of pictures, e.g. 60
pictures or more for obtaining 40 eigenfaces. The training set is
normalized so that all faces are the same scale, position,
orientation, mean, and variance. Face images are read in from a
database. The location of the eyes is identified. In one practice,
an operator uses a mouse to locate manually the eyes in the image
of the face. The face images are converted to gray scale,
normalized, and stored as raw images (as opposed to BMP, or JPEG or
other format). The composition of the training set preferrably
includes examples of types of people expected when the system is
eventually used. For example, men and women, whites, blacks, people
with glasses, people without glasses, people with beards, people
with mustaches, etc. The face images are converted from eight bit
gray scale to floating point format. The mean is found by adding
all the faces together in the training set and then dividing by the
number of face images. The mean is subtracted rom all the face
images. A matrix is formed from the resultant mean adjusted faces.
For example, assume the original face images were 128 pixels by 128
pixels. An entire face image would take up 16384 pixels. Assume
this is a column in a matrix of floating point numbers. Other faces
in the training set make up the other columns in the matrix. The
covariance matrix is computed and the eigenvectors are determined
by solving the Jacobian matrix.
[0044] The eigenvectors can be sorted from large to small and the
most significant eigenvectors are picked according to how many
vectors are wanted, e.g. pick 40 out of 60 if the training set was
60. Using the eigenvectors and the training set, the system
computes the principal components of the original matrix. These are
the "eigenfaces." For example, the system can pick the first
eigenvector which is a vector with 60 elements. An eigenface is
formed by multiplying each face in the training set by the
corresponding coefficient in the eigenvector. Once the eigenfaces
are identified an image signal can be represented as a function of
these eigenfaces by projecting the image signal into the space
defined by these eigenfaces.
[0045] The projected face image represents a point within this
space. In step 130, the verification module verifies that the image
acquired by the image acquisition element 30 is an image of a face
by computing the distance between the point in the space which
defines the acquired image and a portion of the space, a subspace,
that generally indicates that portion of the space onto which an
image of a face maps. In other words, the reference set of
eigenvectors defines an image space into which images captured by
the image acquisition element 30 are mapped. Similar images
generally have similar features and therefore, have similar
coordinates within this image space. Accordingly, similar images,
such as images of people's faces, generally map closely together
within a particular portion of the image space. This defines a
subspace within the image space which is likely to contain similar
types of images. Accordingly, if the point defined by the projected
image is sufficiently distant from the subspace that generally
defines the portion of space where faces generally map onto, then
the verification module determines that the image acquired by the
image acquisition element 30 fails to represent an image of a
person's face. Alternatively, if the point that defines the
acquired image is sufficiently close to, or maps into, the subspace
that generally defines the location of faces, the verification
module verifies that the acquired image represents an image of a
person's face.
[0046] If the verification module, in step 130, verifies that the
acquired image fails to contain, or represent, an image of a
person's face, the process 100 proceeds to step 140. In step 140
the verification module stores the image acquired by the image
acquisition element 30 in a buffer for later use. The verification
module then proceeds to step 150 and activates an enforcement
mechanism which prevents a data record that includes the acquired
image from being generated and entered into the official
database.
[0047] Alternatively, if the verification module in step 130
verifies that the acquired image includes, or represents, the image
of a person's face, the process proceeds to step 160.
[0048] In step 160, the verification module employs the projection
signal, i.e. the image signal encoded as a weighted set of
eigenvectors, or eigenfaces, to search the official record database
to identify any records having a projection signal, i.e. a weighted
set of eigenvectors, similar to the projection signal of the
acquired image. Similar weighting coefficients indicate similar
images. If the verification module in step 170, determines that
there is one or more very similar or duplicate images existing
within the official record database 24, the process proceeds to
step 180, and displays these duplicate images, and then proceeds to
step 190 and activates the enforcement mechanism.
[0049] Alternatively if the verification module, in step 170,
determines that there is no duplicate image within the record
database 24, the verification module verifies that the data record
is to be entered into the database memory 24. In step 200 the
verification module enters the data record within the database
memory element 24. Once the data record is entered, the
verification module proceeds to step 210 and ends the process.
[0050] In one embodiment of the present invention, the enforcement
mechanism includes a display module, that can be an application
program element within the data processor 34, that displays to the
monitor 32 each image within the database stored in memory 24 that
is substantially similar to the image acquired by the camera
element 30. An operator, operating the data acquisition element 22
then compares visually the images already recorded within the
database memory 24 with the individual applicant presently standing
before the image acquisition element 30. At that time, the operator
makes a determination as to whether or not the image of the
applicant is already recorded within the database and verifies if a
demographic data associated with the matching image corresponds
with the demographic data provided by the applicant presently
before the operator. If the demographic data matches or
sufficiently matches the demographic data provided by the
applicant, the operator proceeds to override the enforcement
mechanism and allows the existing data record to be updated with
the information presently provided by the applicant. Alternatively,
if the system operator determines that one or more the images
stored within the database substantially represents the applicant
presently before the image acquisition element 30, and further that
the demographic data provided by the applicant fails to
sufficiently to match the demographic data associated with the
duplicate images, the system operator stores the applicant's image
and new demographic data into an enforcement buffer within the data
processor 34 and can have a law enforcement official issue a
citation to the applicant.
[0051] In a further embodiment of the present invention, the
enforcement mechanism couples to the network job builder 18 that
generates batch commands that operate the recording unit 14 to
manufacture identification cards. In this alternative embodiment,
the enforcement mechanism generates a printer control file that
lists each data record within the database 24 that includes an
image which matches or substantially matches the image of the
applicant. The enforcement mechanism prevents the network job
builder 18 from generating any batch command that would include a
command to generate an identification card for any of these data
records. The enforcement mechanism further generates an enforcement
list, that lists all data records with matching images. This
enforcement list is provided to a law enforcement official for
investigation.
[0052] In a preferred embodiment of the data acquisition element
22, the verification module includes a lensing module that selects
and scales a portion of the acquired image that represents an image
of a person's face. FIG. 3 illustrates a flow chart diagram of one
process 300 that is implemented by the data processor 34 as a
lensing module suitable for practice with the invention.
[0053] The process 300, begins with the step 310 when the image
acquisition element 30 has acquired an image. In a first step, 320,
the process 300 loads a patch of the acquired image into a patch
buffer and determines if this patch contains an image of a person's
face. An image patch is approximately an 80 pixel by 80 pixel patch
of the image captured by the image acquisition element 30. The size
of the patch is generally selected to encompass the area of an
acquired image, of proper scale, that would include a person's face
from approximately the forehead to the lower lip. The process 300
optionally includes a first prefiltering step 330. In step 330, the
data processor determines the mean value of the grey scale of the
pixel elements that makeup the patch presently loaded into the
patch buffer. The data processor 34 compares the mean pixel grey
scale value against a user selected grey scale value and determines
whether or not the patch loaded into the patch buffer is likely to
contain an image of a person's face. In one practice, the mean
pixel grey scale value is compared to a reference pixel value that
represents the average mean pixel grey scale value for twenty
randomly selected images of different faces, i.e. twenty images
where each image represents a different face. If, in step 330, the
mean pixel grey scale value for the patch in the patch buffer fails
to be within a certain range from the reference pixel grey scale
value, the process 300 determines that the patch fails to contain
an image of a person's face and proceeds to step 390. Typically,
the mean pixel grey scale value, prior to normalization, is
approximately 76.37. The standard deviation of the mean is
typically approximately 27.65. In one practice, if the patch is
more that two standard deviations away from the mean value, in
either direction, it is rejected for failing to represent a face.
It should be obvious to one of ordinary skill that these numbers
are empirically determined. Accordingly, different lighting
conditions and other factors can effect these values.
Alternatively, if the process in step 300 determines that the mean
pixel grey scale value is within certain range from the reference
pixel grey scale value, the process determines that the image patch
in the patch buffer may contain an image of a person's face, and
proceeds to step 340.
[0054] In step 340 the process 300 includes a further optional
prefiltering step wherein the process 300 determines if the pixel
grey scale variance, or standard deviation, of the patch loaded
into the patch buffer indicates whether the image patch contains an
image of a person's face. In one embodiment, the data processor 34,
in step 340, determines the pixel variance by the following
formula: 1 ( VAR - AVGVAR ) 2 ( STDDEV of FACES ) 2 : <
THRESHOLD
[0055] where (VAR) represents the pixel variance,(AVGVAR)
represents the average variance, (STDDEV of FACES) represents the
standard deviation of the pixel grey scale value of a face image,
and (THRESHOLD) represents an empirically determined number
representative of the average variance of 20 randomly selected
images of a face.
[0056] If the process 300 determines in step 340 that the variance
of the image patch loaded in the patch buffer fails to indicate
that the patch contains an image of a face, the process 300
proceeds to step 390 that checks if there are remaining patches in
the image that have yet to be tested. Alternatively, if the process
step 300 determines that the variance indicates that the image
patch in the patch buffer could represent an image of a person's
face, the process 300 proceeds to step 350. In step 350 the patch
in the patch buffer is normalized with respect to pixel grey scale
value to have a normalized mean pixel grey scale value and
normalized pixel grey scale variance. In one embodiment, the mean
is adjusted to standardized values by finding the current mean. The
difference between the existing mean and the desired mean is then
added to each pixel value. The standard deviation can be adjusted
to a standardized value by computing the current standard
deviation. The image is then adjusted on a pixel by pixel basis. In
one practice each pixel is adjusted according to the following
procedure:
pixel=(pixel-mean)*(desired_std/current_std)+mean;
[0057] where pixel is the grey scale pixel value; mean is the mean
pixel grey scale value, desired_std is the desired standard
deviation and current_std is the current standard deviation. This
operation can optionally be performed in multiple iterations.
[0058] The process 300 proceeds to step 360 which projects the
normalized image patch into the space defined by the reference set
of eigenvectors, to generate a set of coefficients that represent a
point within the multi-dimensional space defined by the reference
set of eigenvectors. The process 300 includes the optional step 370
that analyzes each of the components of the projection signal and
determines if each projection is reasonable. In one embodiment of
the present invention, the process in step 370 compares each
coefficient of the projection signal to an empirically determined
reference value that represents the average coefficient value of 20
randomly selected projection signals. In one practice, the data
processor 34 in step 370 tests the reasonableness of the
projections in the aggregate. Each projection coefficient has its
empirical mean subtracted from it. The empirical mean represents an
empirically determined value determined from examining the
projection signals of a selected set of face images and determining
the mean value for the coefficients of these projection signals. An
empirical standard deviation can be similarly determined. The
difference between the actual and empirical is squared and divided
by the variance and added to a variable called the significance.
The significance represents a summed value of the deviations of all
the coefficients from their means. The significance can, in one
embodiment be determined according to:
coefficient_delta=proj[i]-projection_mean[i]significance+=(coefficient_del-
ta*coefficient_delta)/ (projection_std[i]*projection_std[i]);
[0059] where coefficient_delta represents the difference between
the actual coefficient and the empirical mean, proj[i] represents
the ith eigenface, projection_mean[i] represents the average
coefficient associated with the eigenface i, projection_std
represents the standard deviation of the ith eigenface.
[0060] The value of the significance for all projections is
compared against an empirical threshold. The value of this
threshold is dependent on the number of eigenfaces used. In one
practice the threshold is set at 25. Accordingly, the generated
coefficients are tested to determine if the projection is
reasonable, i.e. whether the projection signal can be understood to
fall within a user specified range from an empirically determined
value that is generated by computing the average coefficient for 20
randomly selected projection signals. If the process 300 determines
in step 370 that the projection signals are not reasonable, the
process 300 proceeds to step 390 which determines if more image
patches are available to test. Alternatively, if the process 300
determines that the coefficients of the projection signal are
reasonable, the process 300 proceeds to step 380.
[0061] In step 380, the process 300 tests whether the projection
signal generated from the image patch in the patch buffer is
sufficiently close to the portion of the space defined by the
reference eigenvectors and generally indicative of a image
representative of a person's face. In one practice, the process 300
determines the distance of the image from face space by
reconstructing the face using the eigenfaces and subtracting the
resultant reconstruction from the original image, pixel by pixel.
The distance signal represents the sum of the differences over the
entire image. If step 380 determines that the distance between the
point defined by the projection signal and the subspace indicative
of an image of a person's face is greater than an empirically
determined threshold, the process 300 proceeds to step 390 and
determines if more patches are available to examine. Alternatively,
if the distance between the projection signal and the subspace is
sufficiently close to indicate that the patch in the patch buffer
indicates, or represents an image of a face, the process 300
proceeds to step 410 then returns a scale and location factor that
represents the scaling factor applied to the acquired image to
identify a portion of the image representative of a person's face,
and the location within the acquired image, of that portion of the
image that represents a person's face. Alternatively, if the
process 300 in step 380 determines that the distance is
sufficiently large to indicate that the image portion located in
the image buffer fails to indicate an image of a person's face, the
process 300 proceeds to step 390. In step 390 the process 300
determines if there are remaining portions of the image that have
not been tested. If in step 390 the process 300 determines that no
more patches are available, the process 300 proceeds to step 400.
Alternatively, if the step 390 determines that more patches are
available, the process proceeds to step 430.
[0062] In one embodiment of the invention, the software lens is
adjustable and step 430 selects a new patch according to how close
the previous patch was to the face space. The location of the new
patch is offset from the previous patch according to a set number
of pixels, i.e. an offset. The adjustable software lens selects the
offset according to how large the distance signal is. In one
practice, the software lens includes a list of offset values, each
associated with a range of distances. In step 430, the process
selects an offset by identifying which range the distance falls
within and selecting the offset associated with that distance. A
large distance signal can be associated with a large offset and a
small distance signal can be associated with a small offset.
[0063] The process 300 in step 390 selects a new patch for testing,
and proceeds to step 320 which loads the new patch into the patch
buffer. Alternatively, if no more patches are available, the
process 300 proceeds to step 400 and tests whether or not the
search was successful. In step 400 the process 300 determines if
the search was successful by determining if any tested portion of
the acquired image indicated the presence of a person's face, as
represented by a image patch having a mean and a variance that
indicates an image of a person's face within the patch buffer. The
process 300 proceeds to step 420 and adjusts the scaling of the
image within the patch buffer. In one preferred embodiment of the
invention, the data processor 34 adjusts the scaling of the image
in the patch buffer as a function of the distance signal generated
in step 380. For example, if the distance signal indicates that a
projection signal is fairly distant from the portion of space that
generally indicates an image of a person's face, the process 300 in
step 420 significantly adjusts the scaling factor of the image
patch. Alternatively, if the distant signal is relatively small,
the data processor makes a minor adjustment to the scaling factor.
In one practice the scaling factor is selected from a set of
empirically determined values, where each value is associated with
a range of distances. Accordingly, the scale factor is selected by
examining the distance signal and selecting the scale factor
associated with that range.
[0064] Once the process 300 adjusts the scaling factor, the process
proceeds to step 320 and starts all over by loading the first patch
back into the image buffer and testing this patch having resealed
the image.
[0065] In a further alternative embodiment, the process 300 is
adapted to identify a select portion of an image of a person's
face, such as the eyes, the nose or the mouth. In this embodiment,
the process searches an image to identify those portions of an
image representative of the selected facial feature. In this
alternative process, the mean pixel value of the image patch loaded
into the image buffer is compared to a reference mean that
represents an empirically determined standard mean pixel grey scale
value for the portion of an image that contains the selected facial
feature, such as an image of a person's eyes. Similarly, the
variance of the image patch is tested against a reference variance
that represents the variance of the portion of an image that
contains the selected feature. Further, this alternative practice
projects the image patch onto a set of reference eigenvectors
wherein each reference eigenvector is adjusted to represent a
vector in a space computed by reference to a plurality of reference
images each which image represents the selected facial feature. In
practice, this alternative process allows the verification module
to compare select facial features of different images. Accordingly,
a system operator can employ this alternative practice to detect
images recorded in the database memory 24 that have select facial
features which are similar to the facial features of the applicant
standing in front of the image acquisition element 30.
Consequently, the verification module can circumvent the use of
disguises by an applicant attempting to fraudulently obtain
registration into the database stored in memory 24.
[0066] In a further preferred embodiment of the present invention,
the data processor 34 receives the scale factor and location from
the verification module, and stores these values, or signals
representative of these values, within the image file that contains
the image, or signals representative of the acquired image, for
employment by the recording unit 14. In particular, the recording
unit 14 accesses an image file within the image database memory 36,
and records onto a datacard 40 an image representative of the
person's face. The recording unit 14 is preferably adapted to
include a processing unit that accesses the image file stored in
the image database memory 24 to collect both the image information
and the scaling factor and location information. The recording unit
14 employs the scaling factor information and location information
to record the image information in a uniform format onto the
datacard 40. In particular, the recording unit 14 employs the
scaling factor to record the image of the person's face with a
selected scale, i.e. a selected size. Furthermore, the recording
unit 14 employs the location information to identify the center of
the image of a person's face. The recording unit 14 disposes the
center of a person's face at a particular location within the image
recorded onto the datacard 40. Accordingly, the recording unit 14
employs the scaling factor and the location information to generate
a more uniform recorded image, whereby images recorded onto
datacards 40 are of uniform scale and uniform position.
Alternatively, the scaling factor and location information are
provided to the image server 20 or the network job builder 18,
which can adjust the image before transmitting the image to the
recording unit 14. This uniformity of images increases the
difficulty of creating a forged identification card by making it
more difficult to manufacture an identification card that has the
same characteristics as an identification card manufactured by the
authorized system 10.
[0067] In another preferred embodiment of the invention, the data
processor 34 includes a sorting module that employs the
verification module to search and sort images within the image
database memory 24, to identify those images stored within the
image database 24 that fail to represent or include an image of a
person's face. In one embodiment, the system 10 employs the sorting
module to sort a database of images that were loaded into an image
database 24. For example, the system 10 employs the sorting module
to perform an initial search and sort on a set of images that are
loaded into the image database memory 24 from an acquisition
element that does not include an element for verifying that an
image contains or represents a person's face. In operation, the
sorting module selects each image file stored within the image
database memory 24 and, as discussed above with reference to FIG.
3, loads an image patch from the image into a patch buffer. The
verification module examines the loaded image patch to determine if
this image patch contains an image representative of a person's
face. The sorting module proceeds to inspect each image file stored
within the image database memory 24 and generates a list of those
image files that fail to contain an image of a person's face. The
list is provided to a system operator who accesses each image file
and displays the image onto the monitor 32. The system operator
verifies whether or not the image file contains an image
representative of a person's face. Each image file that fails to
contain an image of persons' face is recorded in a list, and the
list is passed to a law enforcement official to determine if a
person has been fraudulently obtaining benefits under this data
record. Accordingly, the sorting module enables the system 10 to
identify those records within an official record that have been
fraudulently entered into an official record.
[0068] Once the data acquisition element has determined that a data
record is to be entered into the official database, the recording
unit 14, vision inspection 12 and packaging unit 16 operate to
generate an identification card that records, typically in a
printed format, the information, or portions of the information,
stored in a data record. Generally, the vision inspection cell 12,
recording unit 14, and packaging unit 16 operate under the control
of the network job builder 18 to generate batch commands, that
represent a series of print commands, wherein each print command
corresponds to a command to generate an identification card that
records onto that card information from one data record.
[0069] To this end, the vision inspection cell 12 connects via an
RS244 port to the network job builder 18. The vision inspection
cell 12 includes a central processing unit 26, a collection unit
28, a support fixture 42, a camera element 44, a cell lighting unit
46, a barcode reader 48, and an image buffer memory 49. The
recording unit 14 includes a central processing unit 50, a data
memory 52, a card source 54, a recorder unit 56, a barcode decoding
unit 58 and an input hopper 60. The packaging unit 16 includes an
output hopper 62, a central processing unit 64, a magnetic stripe
encoder/decoder unit 66, a printer 68 and a packaging assembly unit
70. In an alternative embodiment of the invention, the packaging
assembly unit 70 can further include an envelope sealer and a
postage metering device.
[0070] As depicted in FIG. 1, the network job builder unit 18
connects via a transmission path to the central processing unit 50
of the printing unit 14. In a preferred embodiment of the present
invention the transmission path is an RS244 serial communication
port, and the network job builder unit 18 and the central
processing unit 50 contain RS244 serial interface units. Such
interface units are of the type commonly used in small computer
communications and any of the conventional RS244 communication
units can be practiced with the present invention.
[0071] As previously described, the network job builder 18 can
include a processing unit 18A, a program memory 18B and a data
memory 18C of the type commonly used by data processing devices.
The processing unit 18A connects to the data memory 18C and the
program memory 18B, and operates according to a set of program
instructions stored in the memory 18B to generate a manufacturing
batch file that includes a command field and data field. The
command field includes signals that actuate the recording unit 14
to record on documents, such as the blank cards 40 located in the
card source 54, the one or more data records stored in the data
field.
[0072] The recording unit 14 illustrated in FIG. 1 is a document
manufacture machine of the type suitable for printing in black and
white, or in color. The illustrated recording unit 14 records data
on one or both sides of the document, such as a 2.times.31/2 in.
plastic card, and can record image data, text data and graphic
data. In the depicted embodiment the CPU 50 reads the manufacturing
batch files generated by the network job builder 18 and generates
command signals for the recording unit 56, to record text graphic
and image data onto a blank card 40. The recorder 56 includes a
mechanical linkage for collecting a blank card 40 from a card
source 54 and for moving the card 40 through the recorder 56. The
mechanical linkage assembly (not shown) can include sets of rollers
having textured exterior surfaces suitable for frictionally
engaging a plastic card. The rollers contact the cards 40 in card
source 54 and extract the cards 40 one at a time. The mechanical
linkage assembly moves each card 40 through the linkage assembly
with pairs of rollers radially spaced from each other and connected
to motor assemblies that rotate the rollers in opposing directions.
The rotating rollers feeds the cards 40 one at a time through the
recording unit 14.
[0073] As cards 40 move through the recording unit 14, the recorder
56 records text, graphic, image data or combinations thereof onto
the card 40. The data recorded onto each card 40 corresponds to a
data record stored in the data memory 52. The data record includes
an identification signal that distinguishes one record from the
next. The data record stored in the data memory 52 is typically
part of the manufacturing batch file transmitted from the network
job builder 18. The CPU 50 controls the recorder unit 56 to select
one blank card 40 for each data record stored in the data memory
52. The CPU 50 can control the recorder 56 to record the text,
graphic and image data of one data record onto one card 40 moving
through the recorder unit 56. The recorder 56 can, therefore,
receive one blank card 40 and one data record to generate a data
card 90 having data from that data record recorded thereon.
[0074] The illustrated recorder 56 includes the barcode unit 58.
The barcode unit 58 has a mechanical linkage assembly for
collecting each data card 90 having recorded data and includes a
barcode printer for recording onto each data card 90 a barcode
identification graphic that corresponds to the identification
signal field in the associated data record. In one embodiment of
the present invention the barcode unit 58 records onto the selected
data card 90 a barcode graphic representative of the driver's
license number. The recorded driver's license number is one
identification signal that can uniquely identify each data card 90
being manufactured by the recording unit 14 and the system 10. In
other embodiments and practices of the present invention, the
barcode unit 58 has a mechanical linkage that connects to the input
hopper 60 and that stores completed data cards 90 in the input
hopper 60. The recording unit 14 can be a data card manufacturing
unit of the type conventionally used for producing plastic
identification cards. One such type is the data card 9000 plastic
manufacture machine, sold by the Data Card Corporation in
Minnetonka, Minn.
[0075] In the illustrated embodiment, a collection unit 28 in the
vision inspection cell 12 collects data cards 90 from the input
hopper 60. The collection unit 28 in the illustrated embodiment is
a robotic arm having a robotic end effector with a vacuum cup grip
29 adapted for removing the data card 90 from the input hopper 60.
The robotic arm collection unit 28 collects a data card 90 from the
input hopper 60 and moves the data card 90 in front of the barcode
reader 48. The illustrated barcode reader 48 has a laser scanning
unit for reading a barcode recorded on one side of the data card
90. The barcode reader 48 includes a processing unit for decoding a
barcode graphic recorded onto the data card 90. The decoded barcode
signal representing the decoded information is transmitted to the
CPU 26 and stored in a data memory of the CPU 26. The CPU 26 can
use the barcode information to identify the data record in the
manufacturing batch file, which is associated with the data card 90
held by the robot arm collection unit 28. In one embodiment, the
CPU 26 transmits via the serial interface, a data record request to
the network job builder 18 for the data record associated with the
decoded identification signal. The processing unit 18A of the
network job builder 18 decodes the data record request and
retrieves the corresponding data record from a manufacturing batch
file stored in the data memory 18B, and transmits the data record
to the CPU 26 via the RS-244C interface.
[0076] The vision inspection cell 12 compares the information in
the data record against the information recorded on the associated
data card 90.
[0077] The depicted robot arm collection unit 28 is a TT8010
robotic arm manufactured by the Seiko Instruments Corporation. The
robotic arm is equipped with a vacuum cup end effector adapted for
gripping data cards 90. The vacuum can be generated by a vacuum
pump such as the Fast Vac TT No. VP61-GOH and creates a vacuum
sufficient to hold the card 90. The illustrated cup 29 includes a
vacuum feedback sensor to detect the presence of a data card 90 at
the end effector. The detection of a vacuum at the end effector
indicates that a data card 90 is gripped against the end effector.
The failure to detect a vacuum indicates that a data card 90 is not
present against the cup 29. The vacuum assembly couples via a
transmission path to the CPU 26. The CPU 26 monitors the vacuum
sensor and the sensor element 72 to determine from the position of
the collection element 28 and the presence of a data card 90 at the
cup 29, whether the collection unit 28 is properly moving the data
card 90 through the system 10.
[0078] With reference again to FIG. 1, the illustrated support
fixture 42 has a sensor 74 that connects to the support fixture 42
for being able to detect when a data card 90 has been inserted
therein. The sensor 74 connects via a transmission path to the CPU
26. The CPU 26 can detect the presence of a data card 90 within the
support fixture 42 and activate the camera element 44 to begin the
inspection process.
[0079] In one embodiment of the present invention the camera unit
44 consists of four camera units. Two camera units are arranged
with the support fixture 42 for taking images of the front side of
the data card 90. The two other cameras are arranged with the
support fixture 42 for taking images of the rear portion of the
data card 90. Each set of paired cameras is arranged for taking an
image of the left or right portion of one side of the data card 90.
As depicted in FIG. 1, the camera unit 44 connects via a
transmission path through CPU 26. The CPU 26 can actuate the camera
unit 46 by transmitting a control signal via the transmission path
to the camera unit 44. In one embodiment of the present invention,
the CPU 26 acquires images of the data card 90 in the fixture 42 by
acquiring four images of the card, a front left image, a front
right image, a back left image, and a back right image. The image
data generated by the camera unit 44 is transmitted via the
transmission path to the CPU 26. The program sequence operating the
CPU 26 generates, for each image acquired from the data card 90, a
data file. The data file stores an image signal representative of
the image captured by each camera in the camera unit 44. Each data
file is stored in the data memory of CPU 26. The CPU 26, further
includes an image memory buffer 49. The program sequence operating
the CPU 26, stores in the image memory buffer 49, a copy of the
image signal transmitted from the network job builder unit 18 for
the respective card being manufactured. The CPU 26, generates a
comparison signal by comparing the image data acquired from the
data card 90 in the fixture 42 with the image data used to
manufacture the data card 90 in the recording unit 14 to
manufacture the data card 90. In one preferred embodiment of the
invention, the CPU 26 generates a projection signal from the image
data that represents the image of a person's face and compares the
generated projection signal with a component signal stored in the
image file. If the signals are substantially identical, the CPU 26
generates a signal that verifies that the image has been recorded
correctly, and that the recorded image matches the image of the
data record. Alternatively, the CPU 26 generates an image recording
error signal indicating that the datacard has an error. The
comparison signal is transmitted via the transmission path to the
network job builder 18 and stored in a status file that can be
transmitted to the control image server 20 as a status report.
[0080] As will be described in greater detail hereinafter, the
comparison signal includes a status signal that represents the
status of the document. The status signal indicates whether the
document being inspected has passed or failed the inspection. In
one embodiment of the present invention, if a document fails
inspection three times, the system 10 declares the document is
failed to manufacture and this failure status is sent via the
network job builder 18 to the central image server 20.
Alternatively, the vision inspection cell 12 can generate a
comparison signal having a status signal that indicates that the
document is within tolerance. The vision inspection cell 12 can
send a document successfully manufactured status signal back to the
network job builder 18 and to the control image server 20. Further
the vision inspection cell 12 can transmit the magnetic stripe and
addressing record for the respective document such as a data card
90, to the packaging unit 16. If the document such as the data card
90, is not within tolerance and the vision inspection cell 12
generates a status signal indicating a failed to manufacture
document, the vision inspection cell 12 transmits an invalid
magnetic stripe and addressing record to the packaging unit 16. The
invalid magnetic stripe and addressing record causes the document
to fail the magnetic stripe verification pass within the packaging
unit 16 and the document is rejected and placed within a reject bin
76.
[0081] The illustrated packaging unit 16 is mechanically connected
to the vision inspection cell 12 by the output hopper 62 and is
electronically coupled to the vision inspection cell 12 by the
transmission path that connects CPU 64 with the CPU 26. The
packaging unit includes a unit 66, such as the illustrated magnetic
stripe reader unit 66, that can decode an identification signal,
such as a social security number, recorded onto the data card 90.
The illustrated packaging unit 16 receives a data card 90 through
the output hopper 62 and receives data record files via the
transmission path coupling CPU 64 to CPU 26. The CPU 64 detects the
presence of documents in the output hopper 62 by a sensor mechanism
located within the output hopper 62. The CPU 64 can activate a
mechanical linkage assembly of the type previously described to
remove a data card 90 from the output hopper 62 and to insert the
card 90 into a magnetic stripe unit 66. CPU 64 further collects
from the CPU 26 the data record paired with the document in the
magnetic stripe unit 66. In the illustrated embodiment, the CPU 26
reads the data record from the CPU 50 via the serial interface
transmission path and store the data record in the data memory
within the CPU 64. Alternative data transfer systems for collecting
the data record associated with the identification signal read by
the packaging unit 16 can be practiced with the present invention
without departing from the scope thereof. The illustrated magnetic
stripe unit 66 reads the magnetic stripe on the back of the data
card and transmits the magnetic stripe information to the CPU 64.
The CPU 64 compares the data encoded on the magnetic stripe with
the data in the data record file to verify that the magnetic stripe
has been encoded correctly and to verify that the data card in the
magnetic stripe unit 66 corresponds to the data file stored in the
data memory of CPU 64. If the CPU 64 detects that the magnetic
stripe has been correctly encoded with the information from the
data record and the data memory, a mechanical linkage removes the
card from the magnetic stripe unit 66 to the package assembling
unit 70.
[0082] The CPU 64 transmits via a transmission path, data from the
document file associated with the respective card to the printer
unit 68. The printer unit 68 addresses a document carrier with the
information from the data file. In one embodiment of the invention
CPU 64 transmits one field of information to the printer unit 68,
typically this field of information is the address record for the
data card being manufactured. The printer unit 68 records the
address data onto a document carrier. The document carrier is
transferred via mechanical assembly to the package assembly 70 that
places the data card 90 into the document carrier. A mechanical
assembly collects the document carrier and places the document
carrier with the enclosed data card 90 into the carrier bin 78.
[0083] Alternatively, the packaging unit 16 rejects data card 90
having information misrecorded thereon. In a first practice, the
CPU 64 compares the magnetic stripe data read by magnetic stripe
unit 66 with data from the data file in the CPU 64 memory. CPU 64
detects errors in the recorded magnetic stripe data and transfers
the data card 90 and the magnetic stripe unit 66 via a mechanical
assembly to the reject bin 76.
[0084] In a preferred practice of the invention, CPU 64 rejects
data card 90 to remove from the system 10 those data cards that
fail visual inspection within the vision inspection cell 12. In one
embodiment, the CPU 26 and vision inspection cell 12 detect an
error during the visual inspection of a data card 90. The
collection unit 28 places the data card 90 into the output hopper
62 and the CPU 26 alters the data field for the respective data
card to include a blank signal in the data field. The CPU 26
transfers the data field with the blank signal to the CPU 64 when
the corresponding data card 90 is selected from the output hopper
62 and then placed in the magnetic stripe unit 66. The CPU 64
compares the information encoded on the magnetic stripe with the
blank signal detects the mismatch and activates the mechanical
assembly to remove the data card from the magnetic stripe unit 66
and place the data card into the reject bin 76. In this way, data
cards 90 that fail inspection are sorted out of the successfully
manufactured cards by the packaging unit 16.
[0085] The above description of certain illustrated embodiments is
not intended to limit the scope of the present invention, or to
represent all configurations, practices, or realizations of the
present invention. Furthermore, it should be apparent to one of
ordinary skill in the art of electrical engineering that certain
modifications can be made to the present invention, without
departing from the scope thereof. Accordingly, the scope of the
present invention is to be determined with reference to the
following:
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