U.S. patent application number 11/384984 was filed with the patent office on 2007-09-20 for method, system, and program product for transforming a biometric image.
This patent application is currently assigned to International Business Machines Corporation. Invention is credited to Rudolf M. Bolle, Sharat S. Chikkerur, Jonathan H. Connell, Nalini K. Ratha.
Application Number | 20070217708 11/384984 |
Document ID | / |
Family ID | 38517905 |
Filed Date | 2007-09-20 |
United States Patent
Application |
20070217708 |
Kind Code |
A1 |
Bolle; Rudolf M. ; et
al. |
September 20, 2007 |
Method, system, and program product for transforming a biometric
image
Abstract
The invention provides a method, system, and program product for
transforming a multi-dimensional biometric feature point set. More
particularly, the invention provides a method for transforming a
biometric image using surface folding of the image. In one
embodiment, the invention provides a method for transforming a
multi-dimensional biometric feature point set, the method
comprising: converting the multi-dimensional biometric feature
point set to a canonical position and orientation; applying a
non-invertible transform function to each of a plurality of points
of the biometric feature point set; and providing a transformed
biometric feature point set comprising a plurality of transformed
points.
Inventors: |
Bolle; Rudolf M.; (Bedford
Hills, NY) ; Chikkerur; Sharat S.; (Cambridge,
MA) ; Connell; Jonathan H.; (Cortlandt Manor, NY)
; Ratha; Nalini K.; (Yorktown Heights, NY) |
Correspondence
Address: |
HOFFMAN, WARNICK & D'ALESSANDRO LLC
75 State Street, 14th Floor
ALBANY
NY
12207
US
|
Assignee: |
International Business Machines
Corporation
Armonk
NY
|
Family ID: |
38517905 |
Appl. No.: |
11/384984 |
Filed: |
March 20, 2006 |
Current U.S.
Class: |
382/276 ;
382/115 |
Current CPC
Class: |
G06K 9/0008
20130101 |
Class at
Publication: |
382/276 ;
382/115 |
International
Class: |
G06K 9/36 20060101
G06K009/36; G06K 9/00 20060101 G06K009/00 |
Claims
1. A method for transforming a multi-dimensional biometric feature
point set, the method comprising: converting the multi-dimensional
biometric feature point set to a canonical position and
orientation; applying a non-invertible transform function to each
of a plurality of points of the biometric feature point set; and
providing a transformed biometric feature point set comprising a
plurality of transformed points.
2. The method of claim 1, wherein the non-invertible transform
function includes a point offset direction as a first transform and
a point offset amount as a second transform.
3. The method of claim 1, further comprising: applying the
non-invertible transform function to at least one additional
orientation of each of the plurality of points of the biometric
feature point set.
4. The method of claim 1, wherein applying includes: applying a
first transform function to a position of each of the plurality of
points of the biometric feature point set; and applying a second
transform function to an orientation of each of the plurality of
points of the biometric feature point set.
5. The method of claim 1, wherein the multi-dimensional biometric
feature point set is selected from a group consisting of: a
fingerprint, a facial image, and a signature.
6. The method of claim 1, wherein converting includes: determining
a reference point and a reference orientation.
7. The method of claim 6, wherein the reference point includes a
core of a fingerprint and the reference orientation includes an
orientation of the core of the fingerprint.
8. The method of claim 6, wherein the reference orientation
includes a direction between a core of a fingerprint and a delta of
a fingerprint.
9. The method of claim 1, wherein the non-invertible transform
function includes a mixture of Gaussian kernels.
10. The method of claim 1, wherein the non-invertible transform
function includes a point potential function.
11. A system for transforming a multi-dimensional biometric feature
point set, the system comprising: a system for converting the
multi-dimensional biometric feature point set to a canonical
position and orientation; a system for applying a non-invertible
transform function to each of a plurality of points of the
biometric feature point set; and a system for providing a
transformed biometric feature point set comprising a plurality of
transformed points.
12. The system of claim 11, wherein the non-invertible transform
function includes a point offset direction as a first transform and
a point offset amount as a second transform.
13. The system of claim 11, further comprising: a system for
applying the non-invertible transform function to at least one
additional orientation of each of the plurality of points of the
biometric feature point set.
14. The system of claim 11, wherein the system for applying
includes: a system for applying a first transform function to a
position of each of the plurality of points of the biometric
feature point set; and a system for applying a second transform
function to an orientation of each of the plurality of points of
the biometric feature point set.
15. The system of claim 11, wherein the multi-dimensional biometric
feature point set is selected from a group consisting of: a
fingerprint, a facial image, and a signature.
16. The system of claim 11, wherein the system for converting
includes: a system for determining a reference point and a
reference orientation, wherein the reference point includes a core
of a fingerprint and the reference orientation includes one of: an
orientation of the core of the fingerprint and a direction between
the core of the fingerprint and a delta of the fingerprint.
17. A program product stored on a computer-readable medium, which
when executed, transforms a multi-dimensional biometric feature
point set, the program product comprising: program code for
converting the multi-dimensional biometric feature point set to a
canonical position and orientation; program code for applying a
non-invertible transform function to each of a plurality of points
of the biometric feature point set; and program code for providing
a transformed biometric feature point set comprising a plurality of
transformed points.
18. The program product of claim 17, wherein the program code for
applying includes: program code for applying a first transform
function to a position of each of the plurality of points of the
biometric feature point set; and program code for applying a second
transform function to an orientation of each of the plurality of
points of the biometric feature point set.
19. The program product of claim 17, wherein the biometric feature
point set is selected from a group consisting of: a fingerprint, a
facial image, and a signature.
20. A method for deploying an application for transforming a
multi-dimensional biometric feature point set, comprising:
providing a computer infrastructure being operable to: convert the
multi-dimensional biometric feature point set to a canonical
position and orientation; apply a non-invertible transform function
to each of a plurality of points of the biometric feature point
set; and provide a transformed biometric feature point set
comprising a plurality of transformed points.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Technical Field
[0002] The invention relates generally to biometrics, and more
particularly, to a method, system, and program product for
transforming a biometric image using surface folding.
[0003] 2. Background Art
[0004] Ensuring the privacy of personally-identifiable information
is a growing concern in today's society. Traditional authentication
techniques primarily utilize tokens or depend on some secret
knowledge possessed by a user for verifying his or her identity.
While such techniques have been popular, they suffer from a number
of limitations. Neither token- nor knowledge-based techniques can
differentiate between an authorized user and a person having access
to an authorized user's token or password. In addition,
knowledge-based techniques may require a user to manage multiple
identities (user names, passwords, etc.), limiting the usefulness
of such techniques.
[0005] Biometric authentication and identification techniques based
on a user's physical characteristics (e.g., fingerprints, facial
characteristics, retinal pattern, etc.) overcome the limitations of
token- and knowledge-based techniques. As a result, biometric-based
techniques are rapidly replacing token- and knowledge-based
techniques. However, biometric-based authentication and
identification techniques suffer from their own deficiencies.
[0006] First, biometric data are secure, but not secret. That is,
while biometric data may be unique and inextricably linked to an
individual, some biometrics, such as a voice, facial
characteristics, signature, or fingerprint, may be intercepted in
transmission or mined from a database and subsequently misused by
someone other than the individual.
[0007] Second, biometric data cannot be revoked or cancelled.
Unlike a token or password, which may be revoked, reset, replaced,
etc. in the event that it is lost or otherwise compromised,
biometric data are fixed. As a result, once compromised, biometric
data cannot reliably be used to authenticate or identify the
individual.
[0008] Third, biometric data may be used to track or otherwise
observe an individual without his or her consent. For example, if
the same biometric, such as a fingerprint, is used by more than one
agency, application, or location, it may be possible to track an
individual's movements, transactions, etc. by sharing biometric
data between agencies, applications, or locations.
[0009] In an attempt to overcome these deficiencies, U.S. Pat. No.
6,836,554 to Bolle et al. describes a method for distorting a
biometric, permitting use of the distorted biometric rather than
the original, undistorted biometric. In the event that the
distorted biometric is compromised, it can be revoked and a new
distorted biometric produced using a distortion algorithm different
than was used to produce the first distorted biometric. However,
the distorted fingerprint approach taught by Bolle et al. comprises
scrambled blocks of the undistorted fingerprint. As a consequence,
a slight change in the position of a point of interest in the
undistorted biometric may result in the point of interest being
located in different blocks in the distorted fingerprint. This
makes it difficult or impossible for an authentication device to
identify an individual based on a distorted biometric stored in an
authentication database. In addition, it may be possible to
reconstruct the undistorted biometric from a fingerprint distorted
according to the Bolle et al. block permutation method, thereby
jeopardizing the security of the original biometric.
[0010] To this extent, a need exists for a biometric-based
authentication system and method that does not suffer from the
deficiencies of known systems and methods.
SUMMARY OF THE INVENTION
[0011] The invention provides a method, system, and program product
for transforming a multi-dimensional biometric feature point set.
More particularly, the invention provides a method for transforming
a biometric image using surface folding of the image from which
these points are derived.
[0012] A first aspect of the invention provides a method for
transforming a multi-dimensional biometric feature point set, the
method comprising: converting the multi-dimensional biometric
feature point set to a canonical position and orientation; applying
a non-invertible transform function to each of a plurality of
points of the biometric feature point set; and providing a
transformed biometric feature point set comprising a plurality of
transformed points.
[0013] A second aspect of the invention provides a system for
transforming a multi-dimensional biometric feature point set, the
system comprising: a system for converting the multi-dimensional
biometric feature point set to a canonical position and
orientation; a system for applying a non-invertible transform
function to each of a plurality of points of the biometric feature
point set; and a system for providing a transformed biometric
feature point set comprising a plurality of transformed points.
[0014] A third aspect of the invention provides a program product
stored on a computer-readable medium, which when executed,
transforms a multi-dimensional biometric feature point set, the
program product comprising: program code for converting the
multi-dimensional biometric feature point set to a canonical
position and orientation; program code for applying a
non-invertible transform function to each of a plurality of points
of the biometric feature point set; and program code for providing
a transformed biometric feature point set comprising a plurality of
transformed points.
[0015] A fourth aspect of the invention provides a method for
deploying an application for transforming a multi-dimensional
biometric feature point set, comprising: providing a computer
infrastructure being operable to: convert the multi-dimensional
biometric feature point set to a canonical position and
orientation; apply a non-invertible transform function to each of a
plurality of points of the biometric feature point set; and provide
a transformed biometric feature point set comprising a plurality of
transformed points.
[0016] The illustrative aspects of the present invention are
designed to solve the problems herein described and other problems
not discussed, which are discoverable by a skilled artisan.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] These and other features of this invention will be more
readily understood from the following detailed description of the
various aspects of the invention taken in conjunction with the
accompanying drawings that depict various embodiments of the
invention, in which:
[0018] FIGS. 1A-D show the transformation of a biometric image
according to an embodiment of the invention.
[0019] FIGS. 2A-B show a random distribution of charges.
[0020] FIGS. 3A-B show a mixture of Gaussian kernels.
[0021] FIG. 4 shows a flow diagram of an illustrative method
according to the invention.
[0022] FIG. 5 shows a block diagram of an illustrative system
according to the invention.
[0023] It is noted that the drawings of the invention are not to
scale. The drawings are intended to depict only typical aspects of
the invention, and therefore should not be considered as limiting
the scope of the invention. In the drawings, like numbering
represents like elements between the drawings.
DETAILED DESCRIPTION
[0024] As indicated above, the invention provides a method, system,
and program product for transforming a biometric image. More
particularly, the invention provides a method, system, and program
product for transforming a multi-dimensional biometric feature
point set by, inter alia, applying a non-invertible transform
function to each of a plurality of points in the multi-dimensional
biometric feature point set.
[0025] While described herein with reference to a fingerprint
image, the invention is applicable to the transformation of any
number of biometric images or multi-dimensional biometric feature
point sets, such as a facial image or a signature. For example, in
a facial image the inner and outer corners of the eyes, the tip of
the nose, the bottom of the chin, etc. may be taken as the
biometric feature points. For a signature, the top of each loop,
the position of each pen direction reversal, and the location of
each baseline crossing may be taken as the biometric feature
points. Preferably, the biometric image is two-dimensional,
although three-dimensional biometric images may also be transformed
according to the invention (e.g., the 3D position of the tip of the
nose, chin, etc. as determined from a 3D facial image).
[0026] Turning now to the figures, FIGS. 1A-D show various views of
a fingerprint image during transformation according to one
embodiment of the invention. FIG. 1A shows a fingerprint image 100
suitable for transformation according to the invention. In FIG. 1B,
a reference point (i.e., a core 110) is identified on the
fingerprint image 100. Preferably, at least one reference point is
identified. Where the image is a fingerprint, as in FIG. 1B,
suitable reference points include, for example, a core 110 or a
delta 120.
[0027] In addition, a plurality of feature points 122, 123 are
identified and the position of each feature point defined relative
to the position of at least one reference point 110. This reference
point does not necessarily have to be one of the feature points.
The number of feature points identified will vary based on the
type, quality, and size of the image. Where the image is a
fingerprint, preferably between about 30 and about 80 feature
points are identified. These are commonly referred to as minutia
points and consist of fingerprint ridge endings and ridge
bifurcations.
[0028] In FIGS. 1C-D, the fingerprint image has been removed and
feature points 122, 123 are shown in relation to reference grid
130, 140 respectively. The removal of the fingerprint image 100 in
FIGS. 1C-D is for the purpose of description and simplicity. In
reality, feature points 122, 123 remain disposed in relation to the
fingerprint image 100.
[0029] In order to affect a transformation according to the
invention, each feature point in FIG. 1B is converted to a
canonical position and orientation in FIG. 1C. This is done by
rigidly rotating and translating the whole set of biometric feature
points 122, 123. The translation parameters are chosen so that one
or more of the reference points 110, 120 ends up in a standard
location. The rotation parameter is chosen to align a reference
orientation based on image properties with one of the coordinate
axes. A preferred method is to rotate the whole point set so that
the reflectional symmetry axis of the ridge flow pattern around the
core 110 is vertical. Another preferred method is to rotate the
whole point set so that the line connecting the core 110 and delta
120 is at 45 degrees.
[0030] In FIG. 1C, feature points 122, 123 are shown in relation to
untransformed reference point grid 130. In FIG. 1D, the positions
of feature points 122, 123 are transformed from those shown in FIG.
1C. In order to better show the transformed position of feature
points 122, 123, each is shown in relation to a transformed
reference grid 140. As can be seen in FIG. 1D, the transformation
of feature points 122, 123 resembles a folding of the surface of
transformed reference grid 130 to give reference grid 140.
[0031] The relative horizontal and/or vertical positions of feature
points 122, 123 may be reversed in their untransformed and
transformed states, as though the surface of reference grid 130 was
folded like a sheet of paper. Notice also that several parts of the
original grid 130 may map to the same portion of the distorted
image in FIG. 1D, such as the fold that occurs in the upper right
hand corner. Ambiguities such as this guarantee that the distortion
is non-invertible--there is no way to know which of the original
grid squares in FIG. 1C a point in this region came from.
[0032] One or more feature points may be transformed according to
the invention by adding an offset vector to the feature point's
untransformed position. An offset is computed from a distortion
function, which, in turn, is calculated from a direction value and
a magnitude value. Direction and magnitude values may be based on,
for example, a random distribution of point charges, a mixture of
Gaussian kernels, or a pole-zero model. For example, FIG. 2A shows
a three-dimensional representation of a random distribution of
charges, while FIG. 2B shows the associated two-dimensional
gradient vectors. Similarly, FIG. 3A shows a three-dimensional
representation of a mixture of Gaussian kernels, while FIG. 3B
shows the associated two-dimensional gradient vectors.
[0033] From functions such as those in FIGS. 2A-3B,
transformational direction and magnitude values may be set. For
example, using the random charge distribution of FIG. 2B, a
magnitude value may be set according to the equation: F .function.
( z ) = i = 1 K .times. q i ( z - z i ) 3 , ##EQU1## Here F is the
height of the function in FIG. 2A which can be computed based on
the canonical position of the input biometric feature point z=(x,
y) and a random transformation key [z.sub.1, z.sub.2, . . .
z.sub.K, q.sub.1, q.sub.2, . . . q.sub.K] describing the position
and magnitude of the K charges.
[0034] Similarly, a direction value may be set according to the
equation below which finds a unit vector in the direction of the
gradient shown in FIG. 2B: .PHI. x , y .function. ( z ) =
.gradient. ( i = 1 K .times. q i .times. ( z - z i ) 3 ) ##EQU2##
The new coordinates of a point become z'=(x',
y')=(x+F(z).PHI..sub.x(z), y+F(z) .PHI..sub.y(z)).
[0035] Alternatively, using the mixture of Gaussian kernels shown
in FIG. 3B, a magnitude value may be set according to the equation:
F .function. ( z ) = i = 1 K .times. w i 2 .times. .pi..LAMBDA. i
.times. e - ( z - .mu. i ) T .times. .LAMBDA. - 1 .function. ( z -
.mu. i ) 2 ##EQU3## wherein the random transformation key defines
the parameter of the distributions such as the weights w,
covariances .LAMBDA., and centers .mu. of the K kernels. Similarly,
a direction value may be set according to the equation:
.PHI..sub.x,y(z)=.gradient.F(z).PHI..sub.rand(z), wherein
.PHI..sub.rand is a random phase offset also based on the biometric
feature point's position z. Note that the same random function
would be used each time and that the seed for the random number
generator would become part of the transformation key.
[0036] Direction and magnitude values may be determined according
to the same or different functions. For example, the direction
value may be set according to a random distribution of charges, and
the magnitude value set according to a mixture of Gaussian kernels.
Alternatively, the values may be determined according to, for
example, two different mixtures of Gaussian kernels.
[0037] A preferred embodiment of the invention includes a
transformation utilizing 24 Gaussians, each with the same isotropic
standard deviation of 50 pixels. The centers of the Gaussians are
placed randomly and each given a peak magnitude of +1 or -1. The
additive superposition of all functions is then taken to generate
the function F(z). Preferably, two such surfaces are generated, one
to choose the direction in which each feature point will be moved
by finding the orientation of the local gradient and the second to
choose a magnitude for the transformation of each feature point.
Also, each feature point is moved in the defined direction by at
least a minimum move of 30 pixels.
[0038] Referring now to FIG. 4, a flow diagram of an illustrative
method for transforming a biometric image according to the
invention is shown. In step S1, a set of distinguished biometric
feature points is extracted from the biometric image to represent
the identity of an individual. As noted above, the biometric image
is preferably a two-dimensional biometric image, such as a
fingerprint image. At step S2, at least one reference point and at
least one reference orientation is identified on the biometric
image. At step S3, the point set is rotated and translated based on
the reference point and reference orientation such that it is in a
"canonical" coordinate frame. Next, at step S4, an overall
non-invertible distortion function is calculated based on a
provided key containing the relevant transform parameters. This
distortion function may be based on one or more individual
sub-functions. At step S5, the distortion function is used to
calculate a direction and magnitude for offsetting each of the
biometric feature points. Finally, in step S6 the resulting offset
vectors are applied to the points to produce a new, transformed set
of biometric feature points.
[0039] A biometric image transformed according to the invention
does not suffer from the deficiencies of known methods. For
example, in the case that a transformed biometric according to the
invention is compromised, it may be cancelled, revoked, or
otherwise deactivated and a new transformed biometric produced
simply by altering one or more of the parameters contained in the
distortion key. When transformed with a suitably different set of
parameters, the resulting point set does not match with either the
original point set or with the version of the set resulting from
the previous transform.
[0040] In addition, because transformation methods according to the
invention permit the production of a nearly limitless number of
transformed biometrics, different parameters (keys) may be used by
each individual. Even for the same individual, these parameters
(keys) may be different for each authentication or identification
system with which the user may interact. As a consequence, the
transformed biometric image utilized by each such authentication or
identification system will be unique, eliminating the possibility
that such systems may be combined or otherwise communicate in an
attempt to track a user's movements, transactions, etc. without the
user's consent.
[0041] Finally, the non-invertibility of the transformed biometric
images of the present invention makes it extremely difficult or
impossible to reconstruct the original, untransformed biometric
image. This is a significant advancement over known methods,
greatly improving both the security of biometric authentication and
identification systems, and the willingness of individuals to
utilize them.
[0042] FIG. 5 shows an illustrative system 10 for transforming a
biometric image. To this extent, system 10 includes a computer
infrastructure 12 that can perform the various process steps
described herein for transforming a biometric image. In particular,
computer infrastructure 12 is shown including a computer system 14
that comprises a transformation system 40, which enables computer
system 14 to transform a biometric image by performing the process
steps of the invention.
[0043] Computer system 14 is shown including a processing unit 20,
a memory 22, input/output (I/O) interfaces 26, and a bus 24.
Further, computer system 14 is shown in communication with external
devices 28 and a storage system 30. As is known in the art, in
general, processing unit 20 executes computer program code, such as
transformation system 40, that is stored in memory 22 and/or
storage system 30. While executing computer program code,
processing unit 20 can read and/or write data from/to memory 22,
storage system 30, and/or I/O interface 26. Bus 24 provides a
communication link between each of the components in computer
system 14. External devices 28 can comprise any device that enables
a user (not shown) to interact with computer system 14 or any
device that enables computer system 14 to communicate with one or
more other computer systems.
[0044] In any event, computer system 14 can comprise any general
purpose computing article of manufacture capable of executing
computer program code installed by a user (e.g., a personal
computer, server, handheld device, etc.). However, it is understood
that computer system 14 and transformation system 40 are only
representative of various possible computer systems that may
perform the various process steps of the invention. To this extent,
in other embodiments, computer system 14 can comprise any specific
purpose computing article of manufacture comprising hardware and/or
computer program code for performing specific functions, any
computing article of manufacture that comprises a combination of
specific purpose and general purpose hardware/software, or the
like. In each case, the program code and hardware can be created
using standard programming and engineering techniques,
respectively.
[0045] Similarly, computer infrastructure 12 is only illustrative
of various types of computer infrastructures for implementing the
invention. For example, in one embodiment, computer infrastructure
12 comprises two or more computer systems (e.g., a server cluster)
that communicate over any type of wired and/or wireless
communications link, such as a network, a shared memory, or the
like, to perform the various process steps of the invention. When
the communications link comprises a network, the network can
comprise any combination of one or more types of networks (e.g.,
the Internet, a wide area network, a local area network, a virtual
private network, etc.). Regardless, communications between the
computer systems may utilize any combination of various types of
transmission techniques.
[0046] As previously mentioned, transformation system 40 enables
computer system 14 to transform a biometric image. To this extent,
transformation system 40 is shown including a reference point
system 42, a direction and magnitude value system 44, a distortion
function system 46, and an offset system 48. Operation of each of
these systems is discussed above. Transformation system 40 may
further include other system components 50 to provide additional or
improved functionality to transformation system 40. It is
understood that some of the various systems shown in FIG. 5 can be
implemented independently, combined, and/or stored in memory for
one or more separate computer systems 14 that communicate over a
network. Further, it is understood that some of the systems and/or
functionality may not be implemented, or additional systems and/or
functionality may be included as part of system 10.
[0047] While shown and described herein as a method and system for
transforming a biometric image, it is understood that the invention
further provides various alternative embodiments. For example, in
one embodiment, the invention provides a computer-readable medium
that includes computer program code to enable a computer
infrastructure to transform a biometric image. To this extent, the
computer-readable medium includes program code, such as
transformation system 40, that implements each of the various
process steps of the invention. It is understood that the term
"computer-readable medium" comprises one or more of any type of
physical embodiment of the program code. In particular, the
computer-readable medium can comprise program code embodied on one
or more portable storage articles of manufacture (e.g., a compact
disc, a magnetic disk, a tape, etc.), on one or more data storage
portions of a computer system, such as memory 22 and/or storage
system 30 (e.g., a fixed disk, a read-only memory, a random access
memory, a cache memory, etc.), and/or as a data signal traveling
over a network (e.g., during a wired/wireless electronic
distribution of the program code).
[0048] In another embodiment, the invention provides a business
method that performs the process steps of the invention on a
subscription, advertising, and/or fee basis. That is, a service
provider could offer to transform a biometric image as described
above. In this case, the service provider can create, maintain,
support, etc., a computer infrastructure, such as computer
infrastructure 12, that performs the process steps of the invention
for one or more customers. In return, the service provider can
receive payment from the customer(s) under a subscription and/or
fee agreement and/or the service provider can receive payment from
the sale of advertising space to one or more third parties.
[0049] In still another embodiment, the invention provides a method
of generating a system for transforming a biometric image. In this
case, a computer infrastructure, such as computer infrastructure
12, can be obtained (e.g., created, maintained, having made
available to, etc.) and one or more systems for performing the
process steps of the invention can be obtained (e.g., created,
purchased, used, modified, etc.) and deployed to the computer
infrastructure. To this extent, the deployment of each system can
comprise one or more of (1) installing program code on a computer
system, such as computer system 14, from a computer-readable
medium; (2) adding one or more computer systems to the computer
infrastructure; and (3) incorporating and/or modifying one or more
existing systems of the computer infrastructure, to enable the
computer infrastructure to perform the process steps of the
invention.
[0050] As used herein, it is understood that the terms "program
code" and "computer program code" are synonymous and mean any
expression, in any language, code or notation, of a set of
instructions intended to cause a computer system having an
information processing capability to perform a particular function
either directly or after either or both of the following: (a)
conversion to another language, code or notation; and (b)
reproduction in a different material form. To this extent, program
code can be embodied as one or more types of program products, such
as an application/software program, component software/a library of
functions, an operating system, a basic I/O system/driver for a
particular computing and/or I/O device, and the like.
[0051] The foregoing description of various aspects of the
invention has been presented for purposes of illustration and
description. It is not intended to be exhaustive or to limit the
invention to the precise form disclosed, and obviously, many
modifications and variations are possible. Such modifications and
variations that may be apparent to a person skilled in the art are
intended to be included within the scope of the invention as
defined by the accompanying claims.
* * * * *