U.S. patent application number 09/057847 was filed with the patent office on 2001-08-16 for image processing system with image cropping and skew correction.
This patent application is currently assigned to HEWLETT-PACKARD COMPANY. Invention is credited to SANSOM-WAI, CINDY Y., TRETTER, DANIEL R., WILLIAMS, IRENE H..
Application Number | 20010014183 09/057847 |
Document ID | / |
Family ID | 22013098 |
Filed Date | 2001-08-16 |
United States Patent
Application |
20010014183 |
Kind Code |
A1 |
SANSOM-WAI, CINDY Y. ; et
al. |
August 16, 2001 |
IMAGE PROCESSING SYSTEM WITH IMAGE CROPPING AND SKEW CORRECTION
Abstract
A system and method is described for automatically determining
in a scanned document image the presence of unwanted extraneous
information caused by an extraneous device and scanner background
information. Once the presence of this information is determined,
the system and method of the present invention can compute, for
instance, skew and crop statistics. From this, the image can be
automatically deskewed and cropped appropriately without the
background and extraneous information. The system and method
accomplishes this by first determining the presence of unwanted
extraneous and background information and then appropriately
processing the document image. The extraneous information is
ignored during deskew and crop computations. Also, the scanner
background and the extraneous information are prevented from being
included in the final digital representation of the image.
Inventors: |
SANSOM-WAI, CINDY Y.; (SAN
DIEGO, CA) ; WILLIAMS, IRENE H.; (ESCONDIDO, CA)
; TRETTER, DANIEL R.; (MOUNTAIN VIEW, CA) |
Correspondence
Address: |
HEWLETT PACKARD COMPANY
P O BOX 272400, 3404 E. HARMONY ROAD
INTELLECTUAL PROPERTY ADMINISTRATION
FORT COLLINS
CO
80527-2400
US
|
Assignee: |
HEWLETT-PACKARD COMPANY
|
Family ID: |
22013098 |
Appl. No.: |
09/057847 |
Filed: |
April 9, 1998 |
Current U.S.
Class: |
382/289 |
Current CPC
Class: |
H04N 1/3873 20130101;
H04N 1/387 20130101; G06K 9/32 20130101; G06V 10/24 20220101; H04N
1/3878 20130101; H04N 1/38 20130101 |
Class at
Publication: |
382/289 |
International
Class: |
G06K 009/36 |
Claims
What is claimed is:
1. A method of determining a skew angle of a document image inside
a scan image having a plurality of scan lines of pixels,
comprising: (A) successively receiving scan lines of pixels of the
scan image; (B) comparing a neighborhood of pixels located around a
group of scan lines with predetermined background pixels to define
left and right image boundaries for each group of scan lines; (C)
forming an edge segment by extending an image boundary between
successive groups of scan lines; and (D) determining the skew angle
by calculating an aggregate slope of all edge segments longer than
a predetermined length value.
2. The method of claim 1 further comprising, after step (A) and
before step (B), searching for known characteristics within the
document image and ignoring the known characteristics if found.
3. The method of claim 1, wherein the scan image includes document
image pixels of the document image and background pixels of the
scan image, wherein the step (B) further comprises: (I) receiving a
neighborhood of pixels located around a group of scan lines; and
(II) comparing the group of scan lines of the scan image with
corresponding background pixels to define left and right image
boundaries for each group of scan lines.
4. The method of claim 3, wherein step (II) further comprises: (i)
comparing color of the group of scan lines with color of the
corresponding background pixels; (ii) comparing color of adjacent
pixels of the group of scan lines with color of the corresponding
background pixels; and (iii) confirming the location of an image
boundary when the color of the group of scan lines is different
from that of the corresponding background pixels and the color of
the adjacent pixels are different from that of the corresponding
background pixels.
5. The method of claim 4, wherein the color of each of the
background pixels is approximately one-fourth red, one-half green,
and one-eighth blue.
6. The method of claim 1, wherein step (C) further comprises: (I)
ending the edge segment and generating a new edge segment that
extends from an end scan line of the group of scan lines if the
group of scan lines do not continue the edge segment; and (II)
repeating steps (A), (B) and (C) until all scan lines have been
received.
7. The method of claim 1, wherein step (C) further comprises: (I)
ending the edge segment and generating a new edge segment that
extends from an end scan line of the group of scan lines if the
group of scan lines do not continue the edge segment; and (II)
repeating steps (A), (B) and (C) a predetermined number of
times.
8. The method of claim 1, wherein step (C) further comprises: (I)
ending the edge segment and generating a new edge segment that
extends from an end scan line of the group of scan lines if the
group of scan lines do not continue the edge segment; and (II)
dynamically repeating steps (A), (B) and (C) until an appropriate
number of edge segments has been located.
9. The method of claim 8, wherein the step (D) further comprises:
(a) determining if the document image has a rectangular shape by
determining (1) if the edge segment is at least one of
approximately perpendicular to previous edge segments and
approximately parallel to previous edge segments and (2) if the
edge segment is longer than the predetermined length value; and (b)
setting the skew angle to a predetermined value if the document
image does not have the rectangular shape.
10. The method of claim 9, wherein the skew angle is set to zero if
the document image does not have the rectangular shape.
11. The method of claim 9, wherein the predetermined length value
is approximately equal to twenty five pixels.
12. A method of determining a boundary of a document image inside a
scan image having a plurality of scan lines of pixels, comprising:
(A) checking a neighborhood of pixels located around a group of
scan lines against predetermined background pixels to locate, (1) a
first document image pixel and a last document image pixel for a
first scan line of the scan lines, (2) a first document image pixel
and a last document image pixel of a last scan line of the scan
lines, (3) a leftmost document image pixel of the document image,
and (4) a rightmost document image pixel of the document image; (B)
connecting the first and last document image pixels of the first
and last scan lines, the leftmost document image pixel, and the
rightmost document image pixel together to define the boundary of
the document image.
13. The method of claim 120, further comprising determining if the
document image has multiple skew angles.
14. The method of claim 13, further comprising extending (1) a
first horizontal line through the first and last document image
pixels of the first scan line, (2) a second horizontal line through
the first and last document image pixels of the last scan line, (3)
a first vertical line through the leftmost document image pixel,
and (4) a second vertical line through the rightmost document image
pixel to define the boundary of the document image if the document
image has multiple skew angles.
15. An apparatus, comprising: (A) a storage medium; (B) a computer
executable program stored on the storage medium, the computer
executable program, when executed, determining a skew angle of a
document image inside a scan image having a plurality of scan lines
of pixels, wherein the computer executable program comprises, (I) a
first set of instructions that receives and examines a neighborhood
of pixels located around a group of scan lines of pixels of the
scan image; (II) a second set of instructions that compares a
neighborhood of pixels located around a group of scan lines with
predetermined background pixels to define left and right image
boundaries for each group of scan lines; (III) a third set of
instructions that forms an edge segment by extending an image
boundary between continuous groups of scan lines; and (IV) a fourth
set of instructions that determines the skew angle by calculating
the aggregate slope of all edge segments longer than a
predetermined length value.
16. The apparatus of claim 15, wherein the scan image includes
image pixels of the document image and background pixels of the
scan image, wherein the second set of instructions further
comprises, (a) a first subset of the second set of instructions
that receives a neighborhood of pixels located around a group of
scan lines; (b) a second subset of the second set of instructions
that compares color of the group of scan lines with color of the
corresponding background pixels; (c) a third subset of the second
set of instructions that compares color of adjacent pixels of the
group of scan lines with color of the corresponding background
pixels; and (d) a fourth subset of the second set of instructions
that confirms the location of an image boundary when the color of
the group of scan lines is different from that of the corresponding
background pixels and the color of the adjacent pixels are
different from that of the corresponding background pixels.
17. The apparatus of claim 16, wherein the color of each of the
background pixels is approximately one-half green, one-fourth red,
and one-eighth blue.
18. The apparatus of claim 15, further comprising a first subset of
the third set of instructions that ends the edge segment and
generates a new edge segment that extends from an end scan line of
the group of scan lines if the group of scan lines do not continue
the edge segment.
19. The apparatus of claim 17, further comprising (a) a first
subset of the fourth set of instructions that determines if the
document image has a rectangular shape by determining (1) if the
edge segment is at least one of approximately perpendicular and
approximately parallel to previous edge segments and (2) if the
edge segment is longer than a predetermined length value; and (b) a
second subset of the fourth set of instructions that sets the skew
angle to zero if the document image is not substantially in the
rectangular shape.
20. The apparatus of claim 15, further comprising a fifth set of
instructions that searches for known characteristics within the
document image and ignores the known characteristics if found.
21. An apparatus, comprising: (A) a storage medium; (B) a computer
executable program stored on the storage medium, the computer
executable program, when executed, determines a boundary of a
document image inside a scan image having a plurality of scan lines
of pixels, wherein the computer executable program comprises, (I) a
first set of instructions that checks a neighborhood of pixels
located around a group of scan lines of pixels of the scan image
against predetermined background pixels to locate, (1) a first
document image pixel and a last document image pixel for a first
scan line of the scan lines, (2) a first document image pixel and a
last document image pixel for a last scan line of the scan lines,
(3) a leftmost document image pixel of the document image, and (4)
a rightmost document image pixel of the document image; (II) a
second set of instructions that connects the first and last
document image pixels of the first and last scan lines, the
leftmost document image pixel, and the rightmost document image
pixel together to define the boundary of the document image. (III)
a third set of instructions that searches for known characteristics
within the document image and ignores the known characteristics if
found.
22. The apparatus of claim 18, further comprising a fourth set of
instructions that determines if the document image has multiple
skew angles and a fifth set of instructions that extends (1) a
first horizontal line through the first and last document image
pixels of the first scan line, (2) a second horizontal line through
the first and last document image pixels of the last scan line, (3)
a first vertical line through the leftmost document image pixel,
and (4) a second vertical line through the rightmost document image
pixel to define the boundary of the document image if the document
image has multiple skew angles.
23. The method of claim 2, further comprising performing steps (B),
(C), (D) based on a set of predefined parameters in direct response
to user input regarding the document image.
24. A system for automatically deskewing a scanned document image,
comprising: a boundary defining arrangement for determining
extraneous and background information within a digital
representation of the scanned document image, said boundary
defining arrangement generating an electrical signal indicative of
a plurality of edge segments defining an image boundary of the
scanned document image; and a deskewing arrangement for calculating
an aggregate slope of those individual ones of said plurality of
edge segments exceeding a predetermined length value, said
aggregate slope being indicative of the skew angle of the scanned
document.
25. A method for automatically deskewing a scanned document image,
comprising: generating an electrical signal indicative of a
plurality of edge segments defining an image boundary of the
scanned document image; calculating an aggregate slope of those
individual ones of said plurality of edge segments exceeding a
predetermined length value, said aggregate slope being indicative
of the skew angle of the scanned document; and rotating a digital
representation of the scanned document image by the determined skew
angle.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The present invention pertains to image processing systems.
More particularly, this invention relates to an image processing
system with (1) skew correction that does not require human
intervention or the presence of text or skew detection information
on the original document, and (2) image cropping that is done
regardless of the shape of the image.
[0003] 2. Description of the Related Art
[0004] It has been known that when a document (i.e., the original
physical object, such as photo or text document) is scanned by a
scanner, a digital image of the original document is typically
generated. The digital image of the original document is, however,
often found to be skewed (rotated) inside the entire scan image
(i.e., inside the entire digital image obtained from the scanner).
As is known, the scan image typically includes the image of the
document as well as background information. A skew or inclination
of the document image within the scan image is particularly likely
to occur when the scanner uses an automatic document feed mechanism
to feed the original document for scanning. In addition, when the
size of the original document is relatively small in comparison to
the scan region of the scanner, the scan image may contain
considerable amount of background information.
[0005] For instance, some scanning devices are automatic sheet fed
scanners with stationery charge coupled devices (CCD's). These
scanning devices feed the document past the CCD for scanning. The
document must be grabbed by a set of rollers for scanning. This
mechanism can sometimes scratch the document. Also, small documents
may not be securely grabbed or reliably sensed by the mechanism. In
addition, only a single document at a time can be fed in the
scanner. As a result, document carriers are used to overcome these
problems. A document carrier is usually a transparent envelope
having a white backdrop. The document or documents of interest are
inserted within the envelope for scanning. The document carrier
protects the scanned document from scratches and also provides the
rollers with a larger width original to grab, thereby accomplishing
successful feeding of the document through the scanner.
[0006] However, one disadvantage of using a document carrier is
that the document carrier also becomes part of the scanned data.
For example, if the carrier color does not exactly match the color
of the scanner background, edges of the document carrier will be
contained in the scanned data. This spurious data will cause the
digital image to contain unwanted extraneous information. FIG. 1
illustrates a scan image 100 that exhibits these problems.
[0007] As can be seen from FIG. 1, the scan image 100 contains a
document image 110 of an original document. The remaining area of
the scan image 100 is background 120, which typically has a
predetermined pixel pattern, and extraneous information 140, which
typically has known characteristics. The background 120 can be
caused by the scanner background while the extraneous information
140 can be caused by a document carrier. The document image 110 is
skewed inside the scan image 100 and the background 120 is a
considerable fraction of the scan image 100. When the scan image
100 is displayed on a display or printed by a printer, the document
image 110 typically has a relatively unpleasant and poor visual
quality. In addition, the skewed image may also cause errors when
the image data is further processed by other software programs,
such as optical character recognition programs.
[0008] Techniques have been developed to try to detect and correct
the skew problem. For example, U.S. Pat. No. 4,941,189, entitled
OPTICAL CHARACTER READER WITH SKEW RECOGNITION and issued on Jul.
10,1990, describes a skew correction technique that searches for
text characters along a scan line. As another example, U.S. Pat.
No. 5,452,374, entitled SKEW DETECTION AND CORRECTION OF A DOCUMENT
IMAGE REPRESENTATION and issued on Sep. 19, 1995, describes another
technique that segments the scan image into text and non-text
regions and then determines the skew information based on the
resulting segmentation.
[0009] These techniques, however, require the original document to
contain at least some text. The techniques then rely on the
detection of one or more lines of the text in the document. With
the advent of inexpensive photo scanners and multimedia personal
computers, scanners are nowadays used to scan not only text
documents, but photographs and other image documents as well. The
photographs, however, typically do not contain any text data. This
thus causes the skew detection and correction techniques to be
inapplicable to the scanned photo images. In addition, because
photographs can have a variety of sizes and shapes, it is typically
difficult to trim the background information from the scanned image
of a photograph.
[0010] Another technique has been proposed that detects the skew
information of a scanned image without requiring the presence of
text in the scanned document. One such technique is described in
U.S. Pat. No. 5,093,653, entitled IMAGE PROCESSING SYSTEM HAVING
SKEW CORRECTION MEANS, and issued on Mar. 3, 1992. However, this
technique requires human intervention.
SUMMARY OF THE INVENTION
[0011] Described below is a system and method for automatically
determining in a scanned document image the presence of unwanted
extraneous information caused by an extraneous device, for example,
a document carrier and scanner background information. Once the
presence of this information is determined, the system and method
of the present invention can compute, for instance, skew and crop
statistics. From this, the image can be automatically deskewed and
cropped appropriately without the background and extraneous
information (such as marks from the document carrier). The system
and method accomplishes this by first determining the presence of
unwanted extraneous and background information and then
appropriately processing the document image. The extraneous
information is ignored during deskew and crop computations. Also,
the scanner background and the extraneous information are prevented
from being included with the final digital representation of the
image.
[0012] Specifically, scanner background information and any
extraneous information, such as edges created by the document
carrier, are ignored when processing information is computed, such
as skew and crop statistics, while image edges are retained, such
as document edges of an image or text pages. Thus, the system and
method of the present invention optimizes automatic cropping and
deskewing results of document images scanned by general purpose
scanning devices that are used with or without document
carriers.
[0013] Also, the system and method described below determines a
skew angle of the document image without requiring text in the
document or human intervention. This feature is accomplished by
determining an edge of the document image within a scan image and
using that edge to determine the skew angle of the document image.
The edge can be determined by locating the first or last document
image pixel of each scan line of pixels in the scan image that
belongs to the document image (i.e., the edge pixel of the document
image along that scan line). This is accomplished by comparing a
scan line of pixels with a predetermined scan line of background
pixels or alternatively by comparing a neighborhood around a scan
line with predetermined background pixels. The skew angle of the
document image is then determined by computing the slope of the
detected edge in the scan image.
[0014] In addition, the system and method described below can
determine the boundary of the document image. This feature is
accomplished by locating (1) a first document image pixel and a
last document image pixel for a first scan line of the document
image in the scan image, (2) a first document image pixel and a
last document image pixel of a last scan line of the document image
in the scan image, (3) a leftmost document image pixel of the
document image in the scan image, and (4) a rightmost document
image pixel of the document image in the scan image.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] The present invention is illustrated by way of example and
not by way of limitation in the Figures of the accompanying
drawings, in which like references indicate similar elements, and
in which:
[0016] FIG. 1 shows a skewed image of a document in a scan;
[0017] FIG. 2 shows a computer system that implements an image
processing system;
[0018] FIG. 3 shows the image processing system implemented by the
computer system of FIG. 2, wherein the image processing system
includes an automatic deskew and image cropping system in
accordance with one embodiment of the present invention;
[0019] FIG. 4 illustrates a different configuration of the
automatic deskew and image cropping system in the image processing
system of FIG. 3;
[0020] FIG. 5 shows a document image generated by the image
processing system of FIG. 3 or 4 before being processed by the
automatic deskew and image cropping system of FIGS. 3 and 4;
[0021] FIG. 6 shows the document image of FIG. 5 after being
processed by the automatic deskew and image cropping system of
FIGS. 3 and 4;
[0022] FIG. 7 shows another document image generated by the image
processing system of FIG. 3 or 4 before being processed by the
automatic deskew and image cropping system of FIGS. 3 and 4;
[0023] FIG. 8 shows the document image of FIG. 7 after being
processed by the automatic deskew and image cropping system of
FIGS. 3 and 4;
[0024] FIG. 9A illustrates a sample user interface for implementing
the automatic deskew and image cropping system of FIGS. 3 and
4;
[0025] FIGS. 9B-9C and 10 show flow chart diagrams of the automatic
deskew and image cropping system of FIGS. 3 and 4;
[0026] FIGS. 11 and 12 illustrate calculation of the skew angle and
boundary information of a document image by the automatic deskew
and image cropping system of FIGS. 3 and 4 when the document image
has rectangular and non-rectangular shapes.
DETAILED DESCRIPTION OF THE INVENTION
[0027] The present invention is a system and method for
automatically determining scanner background information and
extraneous information within a digital representation of a scanned
document image. The scanner background information is caused by the
scanner's background and the extraneous information is caused by an
extraneous device, such as a document carrier. For instance, due to
the physical appearance of the document carrier, it can leave marks
within the digital representation of the scanned document image.
Once the presence of this information is determined, the system and
method of the present invention can compute, for instance, skew and
crop statistics. From this, the image can be automatically deskewed
and cropped appropriately without the background and extraneous
information.
[0028] The present invention can be used with general purpose
scanning devices for scanning an image as scanned data input. The
image can be a photograph, multiple photographs in one scan, text
only or mixed documents containing photographs, text, graphics,
etc. The present invention parses the scanned data input for
determining the presence of scanner background information and
extraneous information, which, for example, can be caused by a
document carrier. Also, the scanned data input is parsed for
determining edges and a skew angle of the image. The parsed data is
used to compute skew and crop statistics of the scanned data for
cropping and deskewing the image. This ultimately provides an
aligned digital representation of the scanned image without
unwanted scanner background information and extraneous information.
Specifically, the scanner background and any indicia of an
extraneous device, such as a document carrier, are ignored when the
skew and crop statistics are computed, while image edges are
retained, such as document edges of text pages. Thus, the present
invention properly crops and deskews images scanned by general
purpose scanning devices that are used with or without document
carriers.
[0029] One of the features of the present invention is to provide
skew correction for a scanned image without requiring the presence
of text. Another feature of the present invention is to provide
skew correction for a scanned image without requiring human
intervention. A further feature of the present invention is to
provide image cropping for a scanned image regardless of the size
and/or shape of the original. A still further feature of the
present invention is to provide skew correction and image cropping
for a scanned image in a cost effective manner.
[0030] FIG. 2 illustrates a computer system 200 that implements an
image processing system 320 (shown in FIGS. 3 and 4) within which
an automatic deskew and image cropping system 322 (shown in FIGS. 3
and 4) in accordance with one embodiment of the present invention
may be implemented. Although FIG. 2 shows some of the basic
components of the computer system 200, it is neither meant to be
limiting nor to exclude other components or combinations of
components in the system. The image processing system 320 and the
automatic deskew and image cropping system 322 in accordance with
the present invention will be described in more detail below, also
in conjunction with FIGS. 3 through 12.
[0031] In one embodiment, the computer system 200 can be a personal
computer having a scanner, a notebook computer having a scanner, a
palmtop computer having a scanner, a workstation having a scanner,
or a mainframe computer having a scanner. In another embodiment,
the computer system 100 can be a scan system that also has some or
all of the components of a computer system.
[0032] As can be seen from FIG. 2, the computer system 200 includes
a bus 202 for transferring data and other information. The computer
system 200 also includes a processor 204 coupled to the bus 202 for
processing data and instructions. The processor 204 can be any
known and commercially available processor or microprocessor. A
memory 206 is also provided in the computer system 200. The memory
206 is connected to the bus 202 and typically stores information
and instructions to be executed by the processor 204. The memory
206 may also include a frame buffer (not shown in FIG. 2) that
stores a frame of bitmap image to be displayed on a display 210 of
the computer system 200.
[0033] The memory 206 can be implemented by various types of
memories. For example, the memory 206 can be implemented by a RAM
(Random Access Memory) and/or a nonvolatile memory. In addition,
the memory 206 can be implemented by a combination of a RAM, a ROM
(Read Only Memory), and/or an electrically erasable and
programmable nonvolatile memory.
[0034] The computer system 200 also includes a mass storage device
208 connected to the bus 202. The mass storage device 208 stores
data and other information. In addition, the mass storage device
208 stores system and application programs. The programs are
executed by the processor 204 and need to be downloaded to the
memory 206 before being executed by the processor 204.
[0035] The display 210 is coupled to the bus 202 for displaying
information to a user of the computer system 200. A keyboard or
keypad input device 212 is also provided that is connected to the
bus 202. An additional input device of the computer system 200 is a
cursor control device 214, such as a mouse, a trackball, a
trackpad, or a cursor direction key. The cursor control device 214
is also connected to the bus 202 for communicating direction
information and command selections to the processor 326, and for
controlling cursor movement on the display 210. Another device
which may also be included in the computer system 200 is a hard
copy device 216. The hard copy device 216 is used in the computer
system 200 to print text and/or image information on a medium such
as paper, film, or similar types of media.
[0036] In addition, the computer system 200 includes an image
scanner 218. The image scanner 218 is used to convert an original
document (i.e., the original physical document, such as photo or
text document) into a digitized image which can be further
processed by the computer system 200. In one embodiment, the image
scanner 218 is a fax machine-type image scanner that has a scan
region of one scan line wide. The length of the scan region is the
width of the scan line. In this case, the scan head of the image
scanner 218 simultaneously images the entire scan line. A document
feed mechanism is provided to advance the original document after
each scan. In another embodiment, the image scanner 218 is a
copier-type image scanner that has a relatively large scan region.
For this type of scanner, the original document is placed against
the scan window of the scanner and the scan head of the scanner
moves in one direction after each scan.
[0037] The computer system 200 also includes other peripheral
devices 220. These other devices 220 may include a digital signal
processor, a MODEM (modulation/demodulation), and/or a CD-ROM
drive. In addition, the computer system 200 may function without
some of the above described components. For example, the computer
system 200 may function without the hard copy device 216.
[0038] As described above, the computer system 200 includes the
image processing system 320 (shown in FIGS. 3 and 4) which includes
the automatic deskew and image cropping system 322 of the present
invention (also shown in FIGS. 3 and 4). In one embodiment, the
image processing system 320 is implemented as a series of software
programs that are run by the processor 326, which interacts with
scan data received from the scanner 218. It will, however, be
appreciated that the image processing system 320 can also be
implemented in discrete hardware or firmware.
[0039] Similarly, the automatic deskew and image cropping system
322 alone can be implemented either as a software program run by
the processor 326 or in the form of discrete hardware or firmware
within the image processing system 320. The image processing system
320, as well as the automatic deskew and image cropping system 322,
will be described in more detail below, in the form of software
programs.
[0040] As can be seen from FIG. 3, the image processing system 320
includes a scan control program 324 and an imaging program 326, in
addition to the automatic deskew and image cropping system 322. All
of the programs 322 through 326 are typically stored in the mass
storage device 208 of the computer system 200 (FIG. 2). These
programs are loaded into the memory 206 from the mass storage
device 208 before they are executed by the processor 204.
[0041] The scan control program 324 interfaces with the scanner 218
and the imaging program 326. The function of scan control program
324 is to control the scanning operation of the scanner 218 and to
receive the scan image of an original document 310 from the scanner
218. As is known, the scan image of a document typically includes
the digital image of the document (i.e., the document image) and
some background image and extraneous information if an extraneous
device, such as a document carrier, is used to aid in scanning the
document. The scan control program 324 can be, for example, a
scanner driver program for the scanner 218. Alternatively, the scan
control program 324 can be any known scanner program for
interfacing the scanner 218 with a user.
[0042] As described above, the scan control program 324 controls
the scanner 218 to scan the document 310. The original document 310
can be of different shapes and sizes. For example, the document 310
can be of a rectangular shape, a polygon shape, or a circular or
oval shape. FIG. 5 shows one example of a scan image 500 of the
document 310 obtained by the scan control program 324. As can be
seen from FIG. 5, the document image 502 of document 310 is skewed
inside the scan image 500 and has a skew angle .sub..alpha.. As can
be seen from the scan image 500, the scanned document 310 has a
rectangular shape. FIG. 7 shows another scan image 700 of the
document 310 obtained by the scan control program 324 when the
document 310 has an oval shape. Both FIGS. 5 and 7 show
considerable background within scan images 500 and 700,
respectively.
[0043] As shown in FIG. 3, the imaging program 326 is used in the
image processing system 320 to process the scan image (e.g., the
scan image 500 or 700 of FIG. 5 or 7, respectively) of the original
document 310 received from the scan control program 324. The
imaging program 326 typically processes the scan image of the
original document 310 so that the scan image can be displayed on
the display 210 or printed by the hard copy device 216. The
processing functions of the imaging program 326 typically include
resampling and interpolation of the scan image. The imaging program
326 typically includes a device-specific image driver program. For
example, the imaging program 326 can include a known display driver
program or a known printer driver program. The imaging program 326
can be any image processing application.
[0044] As can be seen from FIG. 3, the automatic deskew and image
cropping system 322 of the image processing system 320 interfaces
with the scan control program 324 and the imaging program 326. The
automatic deskew and image cropping system 322 receives digital
data representing the scan image of the document 310 from the scan
control program 324 and automatically determines the presence of
scanner background information and extraneous information caused by
an extraneous device, such as a document carrier. For instance, due
to the physical appearance of the document carrier, it can leave
marks within the digital data representing the scanned document
image 310. The automatic deskew and image cropping system 322
ignores the scanner background information and extraneous
information and detects the skew angle and boundary of the document
image of the document 310 within the scan image. This provides
correction of the skew of the document image (i.e., deskewed) so
that much or all of the scanner background information and the
extraneous information of the image can be eliminated.
[0045] In the case where a document carrier is used, the document
carrier can cause unwanted extraneous information because it
becomes part of the scanned data. For example, if the carrier color
does not exactly match the color of the scanner background, edges
of the document carrier will be contained in the scanned data. The
present invention detects and deliberately ignores this spurious
data and it is deemed as invalid image data. As a result, the
document carrier information does not influence the results of
other functions and operations of the automatic deskew and image
cropping system 322, such as the automatic crop and deskew
functions (discussed below in detail).
[0046] Many different document carrier sizes exist, and the present
invention is not limited to any particular size. For illustrative
purposes only, two such sizes of document carriers are a full page
carrier, which can be approximately 8.5".times.11" (usually for
text or mixed documents), and a half page carrier, which can be
approximately 8.5".times.5.75" (usually for photos). Typically,
document carriers have some known physical characteristic or
characteristics or some form of indicia that can be used as a basis
to form boundaries within the scanned data. This allows unwanted
document carrier information to be distinguished from wanted image
data. For instance, the bottom of some document carriers contain a
semi-circular notch, which is a known physical characteristic on
all document carriers in that class. The semi-circular notch allows
a user to more easily insert a document into the document
carrier.
[0047] The automatic deskew and image cropping system 322 is
preprogrammed with known physical characteristics of certain
extraneous devices of certain classes. Namely, if a particular
class of document carriers are known to have semi-circular notches,
the automatic deskew and image cropping system 322 is preprogrammed
to indicate that the particular class is associated with
semi-circular notches as a known physical characteristic. If the
known physical characteristic is found after scanning the document
image 310, scanned data representing edges of the document carrier
are located so that the entire unwanted extraneous information
caused by the document carrier is cropped out and discarded.
[0048] Also, because the full size document carrier is too long to
be fed sideways, only one orientation for scanning exists if the
full size document carrier is used. As such, the known physical
characteristic, such as the semi-circle, can only be at the bottom
or top edges and cannot be at the left or right edges. Hence, the
automatic deskew and image cropping system 322 searches for these
known physical characteristics of document carriers, such as
semi-circles, and crops out unwanted information appropriately. By
discarding the edges of the document carrier, additional functions
and operations of the automatic deskew and image cropping system
322 can be performed more accurately.
[0049] The automatic deskew and image cropping system 322 detects
the skew angle of the document image (e.g., the document image 502
of FIG. 5) inside the scan image (e.g., the scan image 500 of FIG.
5) by first detecting an edge of the document image and then
determining the slope of the edge. This allows the skew angle
detection of the document image to be done without requiring the
presence of text or special skew detection marks on the document
image. This also allows the imaging program 326 to correct the skew
of the document image without human intervention.
[0050] In addition, the automatic deskew and image cropping system
322 detects the boundary of the document image (e.g., the document
image 502 of FIG. 5). There are several ways that the automatic
deskew and image cropping system 322 detects the boundary of the
document image. Two sample techniques are discussed in detail below
for illustrative purposes only. Each technique can be custom
configured for specific implementations. The first sample technique
detects the boundary by locating a first and a last document image
pixel for the first scan line of the document image, a first and a
last document image pixel for the last scan line of the document
image, a leftmost document image pixel of the document image, and a
rightmost document image pixel of the document image within the
scan image. The positioned information of these six pixels is then
used to compute the extent (i.e., boundary) of the document image
in the scan image after skew correction. This information is then
provided to the imaging program 326, allowing the imaging program
326 to trim or crop the scan image to obtain the document image
without much or all of the background information.
[0051] The automatic deskew and image cropping system 322 detects
the skew angle and boundary information of a document image within
a scan image by locating the first and last pixels of each scan
line of the document image inside the scan image. The automatic
deskew and image cropping system 322 can accomplish this by
comparing each scan line of pixels in the scan image with a
predetermined scan line of background pixels to locate the first
and last document image pixels. This can alternatively, and
preferably, be accomplished by comparing a neighborhood around each
scan line of pixels in the scan image with predetermined background
pixels to locate the first and last document image pixels. This
allows boundary edge segments of the document image to be
developed. The automatic deskew and image cropping system 322 then
determines the length of each edge segment of the document image
and calculates the skew of the edge segment. If the automatic
deskew and image cropping system 322 determines that an edge
segment is not long enough, the program 322 does not calculate the
skew of that edge segment.
[0052] In addition, if the automatic deskew and image cropping
system 322 determines that the document image has multiple skew
angles (i.e., the skew of an edge segment in the document image is
not equal to that of another edge segment of the document image),
the program 322 determines that the document image has a
non-rectangular shape. When this occurs, the automatic deskew and
image cropping system 322 sets the skew angle of the document image
to .sub..theta., which is preferably zero, whether the document
image is skewed or not. In other words, if the automatic deskew and
image cropping system 322 determines that the document image has a
non-rectangular (e.g., circular, oval, or polygonal) shape, the
program 322 preferably does not detect the skew angle of the
document image. Instead, the program 322 provides the boundary
information of the document image so that much or all of the
background can be trimmed or cropped away from the scan image.
[0053] Moreover, when the automatic deskew and image cropping
system 322 determines that the detected document image is not of a
rectangular shape, the program 322 preferably defines the smallest
rectangle that contains all of the six boundary pixels and informs
the imaging program 326 to take the entire interior of this
rectangle as the cropped document image (see, for example, FIG. 8).
In this case, not all background information is trimmed off. The
operation of automatic deskew and image cropping system 322 is now
described in more detail below, also in conjunction with FIGS. 5-6
when the document 310 has a rectangular shape or FIGS. 7-8 when the
document 310 has a non-rectangular shape.
[0054] As can be seen from FIGS. 3 and 5-6, the skew detection and
image cropping program 322 checks the scan image 500 to locate the
first and last document image pixels of the first scan line of the
document image 502. As can be seen from FIG. 5, the program 322
learns that the first scan line of the scan image 500 is the first
scan line of the document image 502. The program 322 then locates
the first document image pixel 518 and the last document image
pixel 520 of the first scan line of the document image 502. As the
automatic deskew and cropping system 322 continues checking the
first and last document image pixels of other scan lines of the
document image 502, edge segments 510, 512, 514, 516 are developed.
In addition, the leftmost document image pixel 521 and rightmost
document image pixel 522 are located. The first and last document
image pixels (i.e., 524 and 526) of the last scan line of the
document image 502 are also located. As can be seen from FIG. 5,
the first document image pixel 524 of the last scan line of the
document image 502 overlaps the last document image pixel 526 of
that scan line.
[0055] After the edge segments 510, 512, 514, 516 of the document
image 502 are developed, the automatic deskew and cropping system
322 calculates the skew angle .sub..alpha. which is then sent to
the imaging program 326 (FIG. 3), along with cropping boundaries
computed from the skew angle .sub..alpha. and the pixels 518, 520,
522, 524, 526.
[0056] As described above, the automatic deskew and cropping system
322 of FIG. 3 also detects if the document image is of a
rectangular shape when the program calculates the skew angle
.sub..alpha. of the document image. If the program 322 detects that
the document image (e.g., the document image 702 of FIG. 7) is not
of a rectangular shape, then the program 322 preferably does not
calculate the skew angle of the document image and preferably sets
the skew angle to zero. The automatic deskew and cropping system
322 detects whether a document image is rectangular or not by
determining if the document image has multiple skew angles. When
this occurs, the document image has a non-rectangular shape (e.g.,
the polygonal shape). In addition, the program 322 also detects if
the document image has a rectangular shape by detecting if the edge
segments of the document image are longer than a predetermined
length. Those edge segments shorter than the predetermined length
are discarded, and no skew angle is computed for such segments. If
all detected segments are discarded, the program 322 determines
that the document image has a non-rectangular shape (e.g., oval or
circular shape) and again does not calculate the skew angle of the
document image. When this occurs, the program 322 preferably
locates those six boundary pixels of the document image. FIGS. 9A
through 10 show in flow chart diagram form the automatic deskew and
cropping system 322, which will be described in more detail
below.
[0057] As can be seen from FIGS. 3 and 7-8, when the document 310
has a document image 702 that is of an oval shape, the program 322
of FIG. 3 detects multiple edges that are of different skew angles
and/or shorter than the predetermined edge length. In one
embodiment, the predetermined edge length contains approximately
twenty five pixels. In alternative embodiments, the predetermined
edge length can be longer or shorter than twenty five pixels.
[0058] When the program 322 detects that the document image 702 is
not rectangular, the program 322 preferably locates the six
boundary pixels (i.e., the first and last document image pixels 710
and 712 of the first scan line of the document image 702, the
leftmost document image pixel 714, the rightmost document image
pixel 716, and the first and last document image pixels 718 and 720
of the last scan line of the last scan line of the document image
702. As can be seen from FIG. 7, the first and last document image
pixels 710 and 712 of the first scan line of the document image 702
overlap each other and the first and last document image pixels of
the last scan line of the document image 702 overlap each
other.
[0059] As can be seen in FIGS. 3 and 5-6, the imaging program 326
then corrects the skew of the document image 502 in accordance with
the skew angle .sub..alpha. received from the automatic deskew and
cropping system 322 and eliminates all of the background 504 in the
scan image 500 in accordance with the six document image pixels
518-526. The imaging program 326 does this in a known way, which
will not be described in more detail below. The processed document
image 600 is shown in FIG. 6.
[0060] As can be seen from FIGS. 5 and 6, the processed document
image 600 of FIG. 6 is identical to the unprocessed document image
502 of FIG. 5 except that no background information of the scan
image 500 is displayed in FIG. 6. In addition, the processed
document image 600 is not skewed. Moreover, the processed document
image 600 of FIG. 6 does not have the cut-off edge. This is due to
the fact that the imaging program 326 further trims the document
image 502 of FIG. 5 based on the document image pixels 518-526.
[0061] When processing the document image 702 of FIG. 7, the
automatic deskew and cropping system 322 (FIG. 3) only sends the
pixel information of the six boundary pixels 710 through 720 to
imaging program 326 (FIG. 3). Based on these six pixels 710-720,
the imaging program 326 creates a smallest rectangle 800 that
contains all of these pixels and the document image 702. The
imaging program 326 then trims away everything in the scan image
700 of FIG. 7 that is outside of the rectangle 800 to obtain the
cropped document image 702.
[0062] As can be seen from FIG. 3, because the automatic deskew and
cropping system 322 interfaces with the scan control program 324,
the automatic deskew and cropping system 322 receives one scan line
of pixels from the scan control program 324 as soon as the scan
control program 324 controls the scanner 218 to finish scanning one
such scan line. This causes the automatic deskew and cropping
system 322 to operate in parallel with the operation of the scan
control program 324. As a result, the automatic deskew and cropping
system 322 can determine the skew angle and boundary information of
the document image of the document 310 as soon as the scan control
program 324 finishes scanning the document 310.
[0063] It is, however, appreciated that the automatic deskew and
cropping system 322 is not limited to the above described
configuration. FIG. 4 shows another embodiment of the image
processing system 320 in which the automatic deskew and cropping
system 322 only interfaces with the imaging program 326. This
allows the automatic deskew and cropping system 322 to detect the
skew angle and boundary information of the document image of the
document 310 after the entire document 310 has been scanned and its
scan image has been sent to the imaging program 326 from the scan
control program 324.
[0064] FIG. 9A illustrates a sample user interface for implementing
the automatic deskew and image cropping system of FIGS. 3 and 4.
The present invention increases user ease by automatically
deskewing and cropping scanner background information and
extraneous information (although automatic functions can be
disabled, if desired). For automatic operation, the system starts
810 a user is given options for specifying a type of document to be
scanned, such as text only, mixed format, photo only, custom
options, etc., and the automatic deskew and cropping system 322
finds the best crop and deskew operation. The options can be
presented in two tiers. The first tier allows novice users to
simply specify the kind of document they are scanning (photo only,
mixed document, etc.). The second tier allows more sophisticated
users to further customize processing.
[0065] Namely, several options can be presented to a user. These
options increase processing flexibility for the user. First, second
and third options 812, 814, 816 can be for novice users and a
fourth option 818 can be for advanced users with customization
functions. The first option 812 can be for images that contain text
only and the second option 814 can be for mixed formats (for
example, images that contain a combination of photographs, text,
graphics, etc). For the first and second options 812, 814,
automatic deskew and cropping functions are preferably disabled 815
and the routine ends 817. The third option 816 can be for images
that contain only photos. If the user chooses the fourth option
818, the user can be presented with three customization
sub-options. A first sub-option 820 for images that contain only
photos, a second sub-option 822 for mixed formats and a third
sub-option 824 for manually disabling the automatic functions 826
after which, the routine ends 828.
[0066] If the third option 824 and the first sub-option 820 are
chosen, an automatic skew and crop detection step 830 is performed
based on a first set of predefined parameters (discussed below in
detail). If the second suboption 822 is chosen, an automatic skew
and crop detection step 832 is performed based on a second set of
predefined parameters (discussed below in detail). The automatic
deskew and cropping system 322 determines the boundaries and
location of the scanner background and extraneous information, if
it exists. As discussed above, the extraneous information can be
caused by a document carrier. The document carrier information is
found based on the first and second set of predefined parameters
(discussed below in detail). Next, the automatic deskew and
cropping system 322 performs an automatic deskew and cropping (crop
out portions of the scanned data that are not part of the photo)
function as steps 834 and 836, the routing then ends 838. For
example, during cropping, unwanted scanner background or document
carrier information will be automatically cropped out. In addition,
the automatic functions provide cropping for multiple photos being
scanned as a single page. In this case, regions outside of the
multiple photos are cropped out.
[0067] The following description is for illustrative purposes only.
The extraneous device can be any extraneous device and does not
have to be a document carrier. Specifically, if a document carrier
is the extraneous device causing the extraneous information,
depending on the option chosen by the user, the automatic deskew
and cropping system 322 searches for the known physical
characteristics of the particular document carrier. For instance,
if the user chooses the third option or the first sub-option, for
example, for photos only, the automatic deskew and cropping system
322 searches for either a half or full size document carrier. This
is because a user could utilize either the half or full size
document carrier for a photo. Similarly, if the user chooses the
second sub-option, for example for mixed formats, the automatic
deskew and cropping system 322 preferably searches for a full size
document carrier. This is because a mixed document typically is too
large for the half size document carrier. Therefore, a search is
preferably performed for either the half or full size document
carrier if the third option or the first sub-option (photo only) is
chosen while a search is preferably performed for the full size
document carrier if the second sub-option (mixed format) is
chosen.
[0068] For the half size document carrier, an initial search is
performed for known physical characteristics, such as a semicircle
at the bottom, top, right, or left edges. This is because some
document carriers, such as the half size document carrier, can be
fed into the scanner device in any orientation. As a result, the
known physical characteristic, such as the semicircle, can appear
at the bottom, top, left or right edges of the scan. For the full
size document carrier, an initial search is performed for known
physical characteristics, such as a semicircle at the bottom or top
edges. This is because some document carriers, such as the full
size document carrier, can be fed into the scanner device in only
two orientations. As such, the known physical characteristic, such
as the semicircle, can appear only at the bottom or top edges of
the scan.
[0069] If the known physical characteristic is found, scanned data
representing edges of the document carrier are ignored during
computation of skew and crop statistics, and are eventually cropped
out and discarded as unwanted information of the scan. Also,
because the full size document carrier is too long to be fed
sideways, only one orientation for scanning exists if the full size
document carrier is used. As such, the known physical
characteristic, such as the semi-circle, can only be at the bottom
or top edges and cannot be at the left or right edges. Hence, the
present invention searches for these known physical characteristics
of document carriers, such as semi-circles, and crops out unwanted
information appropriately. By ignoring the edges of the document
carrier, more accurate automatic deskewing and cropping of the
information of interest can be performed.
[0070] FIGS. 9B and 9C show the process of the automatic deskew and
cropping system 322 (FIGS. 3 and 4) in developing the edge segments
and the six boundary pixels of the document image. FIG. 10 shows
the process of the system 322 of FIGS. 3 and 4 in detecting the
skew angle of the document image based on the edge segments
developed by the process of FIGS. 9B and 9C. FIG. 11 shows how edge
segments are developed in a rectangular document image. FIG. 12
shows how edge segments are developed in a circular or oval
document image. FIGS. 9B, 9C and 10 will be described in more
detail below, also in connection with FIGS. 11 and 12.
[0071] In one embodiment, an edge of the document image is
determined within a scan image and that edge is used to determine
the skew angle of the document image. The edge can be determined by
locating the first or last document image pixel of each scan line
of pixels in the scan image that belongs to the document image
(i.e., the edge pixel of the document image along that scan line).
This is accomplished by comparing each scan line of pixels with a
predetermined scan line of background pixels. The skew angle of the
document image is then determined by computing the slope of the
detected edge in the scan image.
[0072] In another embodiment, a pixel of a scan line is regarded as
an image pixel when its color is different from the color of the
corresponding reference background pixel by more than the
predetermined threshold value and the color of its adjacent pixel
is also different from the color of the corresponding reference
background pixel by more than the predetermined threshold value. In
other words, small groups of pixels are analyzed together, such as
a neighborhood of pixels. This can be accomplished by using a
sliding window of pixels. This increases accuracy and more readily
distinguishes actual wanted document data from unwanted extraneous
information and background noise. This embodiment is more robust in
the presence of scanner noise.
[0073] Specifically, as can be seen from FIGS. 9B and 9C, the
process starts at step 900. At step 902 color values of background
pixels are set. At step 904 variables are initialized and a
neighborhood size is defined. The neighborhood size can be defined
with a pixel size having a neighborhood height of pixels and a
neighborhood width of pixels (n.sub.h rows, n.sub.w columns). The
values are set as the reference values for comparing with the
colors of the pixels of a neighborhood around each scan line of the
scan image to locate the first and last image pixels (i.e., edge
pixels) of each scan line. In another embodiment, only the
luminance valve of each pixel is used, where luminance is computed
as approximately one-fourth red, one-half green, and one-eighth
blue. In one embodiment, a pixel is regarded as an image pixel when
its color (or luminance) is different from the color (or luminance)
of the corresponding reference background pixel by more than a
predetermined threshold value. The term color will be used
hereinafter interchangeably to mean color and/or luminance. The
threshold value is typically a constant that is determined based on
the expected variability of the scanner background.
[0074] At step 906, a sliding window can be set up as a
neighborhood of pixels comprised of several rows, such as two,
three, four, etc. rows. The size of the sliding window or
neighborhood of pixels can be adjusted to suit certain conditions.
For example, a larger neighborhood of pixels can be used when a
photograph is to be scanned. In contrast, a smaller neighborhood of
pixels can be used when a mixed document is to be scanned. It
should be noted that the neighborhood of pixels for a mixed
document should not exceed a maximum predetermined value. This is
because text data could be mistaken as background noise if a
neighborhood of pixels that is too large is used. The neighborhood
of pixels can be defined with a size having a neighborhood height
and a neighborhood width (n.sub.h rows, n.sub.w columns).
[0075] At step 908, it is determined if all of the scan lines of
the scan image have been processed. If so, steps 910-914 are
performed to calculate the skew angle of the document image inside
the scan image. As can be seen from FIG. 9B, step 912 is employed
to determine if the document image is of non-rectangular shape. The
program 322 (FIGS. 3 and 4) does this at step 912 by determining if
different skew angles are found for the edge segments of the
document image. If so, the program 322 does not calculate the skew
angle of the document image. Instead, the skew angle is set to zero
in step 916. If, at step 912, it is determined that these are not
multiple skew angles, then step 914 is performed to calculate the
skew angle of the document image. In either case, the program 322
finishes by computing the cropping boundaries in step 917 and
ending at step 954.
[0076] When, at step 908, if it is determined that the scan image
has not been completely checked, step 918 is then performed to
obtain the neighborhood around the next unchecked scan line of
pixels (e.g., scan row r). Next, although the sliding window is
initially set at some number, at step 920 the sliding window is
incremented every time a scan line is checked so that row r is
appended to the bottom of the sliding window and the topmost row is
deleted. A color of a neighborhood around each of the pixels of the
scan row r is then compared with a color of predetermined
background pixels at step 922 to determine if they match. In other
words, for a neighborhood of three rows, rows r, r-1, r-2 are
compared to predetermined background pixels. If they match, (i.e.,
rows r-n.sub.h+1 through r contains substantially background pixel
values), then the program 322 returns to step 908 via step 924. If
not, step 926 is performed, at which the first document image pixel
(i.e., pixel c1) where a neighborhood index, such as row r and
column c1 having a color different from that of the corresponding
background pixel is located. In this case, row r and column c1
indicates a lower corner. However, this row is arbitrary and any
row could be used for the neighborhood index, as long as it is the
same all of time.
[0077] The process then moves to step 928, at which the boundary
pixel storage is updated. This is done by comparing the current
first and last pixels with the stored six boundary pixels to
determine if these six pixels need to be updated. The positioned
values of these six pixels are initially set at zero. If, for
example, the positional value of the current first pixel is less
than that of the stored leftmost pixel, then the stored leftmost
pixel is replaced with the current first pixel. This allows the six
boundary pixels of the document image to be finally determined.
[0078] Then step 930 is performed, at which it is determined if
neighborhood index (r, c1) continue a left edge segment. If so,
step 934 is performed to continue the edge segment by adding
neighborhood index (r, c1) to segment the edge segment. For
example, as can be seen from FIG. 11, with image pixels 1070 and
background pixels 1080, if scan line 1100 is currently checked and
pixel 1106 is determined to be the first pixel of the scan line
1100. Step 930 of FIG. 9C then determines if the pixel 1106
continues the edge segment 1102 and causes the edge segment 1102 to
extend from the pixel 1106. However, edge segments are preferably
allowed to skip a predefined number of rows if subsequent rows are
not aligned. This is because random noise can cause one or several
rows to temporarily misalign or diverge for only a few rows. In
this case, the edge segment should continue. FIG. 12 shows the
development of edge segments 1200 and 1202 of a circular or oval
document image. Similarly, edge segments are preferably allowed to
skip a predefined number of rows if subsequent rows are not
aligned.
[0079] Thus, as can be seen from FIG. 9C, when the answer is no at
step 930, it is determined in step 932 whether a predefined number
of rows has been exceeded. If so, step 936 is then performed to end
that left edge segment. Step 938 is then performed to start a new
left edge segment from this first pixel. If a predefined number of
rows has not been exceeded, then steps 940 through 952 are
performed so that a last neighborhood column index c2 is located
where a color differs from that of the corresponding background
pixel. As can be seen from FIGS. 9B-9C, steps 940-952 are basically
the same steps as steps 926-938, except that steps 940-952 are
employed to locate and process the last pixel of the scan line
while steps 926-938 are employed to locate and process the first
pixel of the scan line. Also, steps 926-938 can be performed in
parallel with steps 940-952. In other words, steps 940-952 do not
have to be performed sequentially after steps 926-938.
[0080] FIG. 10 shows the process of updating the skew information
based on a detected edge segment. This process is undertaken when a
segment is ended, as in steps 910, 924, 936, and 950 of FIGS. 9B
and 9C. The routine starts 1000 and it is determined in step 1002
whether multiple skews have already been found. If so, the routine
ends at step 1014. If not, whenever the segment is too short, it is
discarded in step 1004. If the segment is long enough, a numerator
and denominator ratio are determined at step 1006. Next, if the
ratio is too different from that of a previous segment, or in other
words, if the document image is determined to have a
non-rectangular shape in step 1008, the skew angle is set to zero,
and subsequent segments are discarded in step 1010. Otherwise, the
slope of the detected segment is used to update the skew angle
estimate in step 1012 and the routine then ends in step 1014.
[0081] In addition, in typical scanner devices, the user is
permitted to change brightness settings, which alters the luminance
values of the scanned data. Since the automatic deskew and cropping
system 322 can use luminance values to perform edge detection, the
automatic deskew and cropping system 322 performs dynamic
adjustment of background threshold values to match changes in
brightness settings. Moreover, the user is usually permitted to
change color/grayscale mode settings (such as 24 bit color or 8 bit
grayscale scans), which alters the luminance values of the scanned
data since the luminance values of grayscale images are different
from the color images. The automatic deskew and cropping system 322
performs dynamic adjustment of threshold values to match changes in
color/grayscale mode settings.
[0082] In the foregoing specification, the invention has been
described with reference to specific embodiments thereof. It will,
however, be evident to those skilled in the art that various
modifications and changes may be made thereto without departing
from the broader spirit and scope of the invention. The
specification and drawings are, accordingly, to be regarded in an
illustrative rather than a restrictive sense.
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