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Description  |
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BACKGROUND OF THE INVENTION
The present invention relates generally to image joining method and
apparatus. More particularly, the invention is concerned with an image
joining scheme suited profitably for inputting a picture or image of a
large size such as a newspaper size, A2 size, A3 size or the like by using
a small type image input device such as a scanner for A4 size or the like.
In recent years, a document image file system (electronic file) in which an
optical disc of a large capacity is employed attracts public attention as
novel document managing means. The range of application of such document
image file system tends to be increasingly widen, and there arises a
demand for the capability of filing pictures or images of large size such
as that of a newspaper, an architectural drawing or the like, as they are.
For meeting the demand, there has been developed a large size image input
or reading device such as an Al-scanner, as exemplified by "Al Scanner
(HT-4634-11)" for a file "HITFILE 650" commercially available from Hitachi
Co. of Japan.
SUMMARY OF THE INVENTION
The hitherto known large size image input or reading apparatus mentioned
above suffers from problems jn that it involves high manufacturing cost
and requires large space for installation because of large input or
reading surface area on the order of A1 size.
Accordingly, an object of the present invention is to provide an image
joining system which allows a picture or image of a large size such as A1
size to be inputted and stored by using an image input (reading) apparatus
of a relatively small size such as for A4 size or smaller which can be
manufactured at lower cost.
In the course of studying and developing a means which allows a large size
image to be inputted or read by an image input apparatus of a relatively
small size, the inventors of the present application got idea of dividing
a large size image to be inputted into a plurality of image portions,
which are then sequentially inputted, whereon the inputted image divisions
or portions are joined together to thereby restore the original large size
image. In that case, the original image of large size should be restored
without any appreciable distortions and with high accuracy.
It is therefore another object of the present invention to provide an image
joining system which is capable of restoring an original image of large
size with high accuracy after it has been inputted through division.
In view of the above and other objects which will be more apparent as
description proceeds, there is provided according to an aspect of the
present invention an image joining system in which an image to be inputted
(original image) of a greater size than that of input surface area of an
image input device such as a scanner or the like is divided into a
plurality of image portions which are then sequentially inputted through
the abovementioned image input device, whereon the input image portions
(divided images) are joined together to one image on image storing means
(memory) by matching the positions of the individual image portions by
making use of detectable graphic patterns such as marks each indicating a
reference point for the joining.
For realizing the position matching of the individual image portions with
the aid of the marks, seals each printed with a detectable mark indicating
a reference point for the image joining may be attached to an overlap
region of each of the individual image portions to be joined together or
the image to be inputted is placed on a carrier (such as carrier sheet,
pass case or the like) printed with similar marks, whereon the image of
concern is inputted by dividing it in such a manner in which the regions
covering the mark positions overlap each other.
For matching the positions of two image portions inputted by dividing an
image to be inputted there may be adopted a mark center position detecting
method based on a structural analysis, a least pixel change line detecting
method, a greatest white line detecting method, a logical sum (ORing)
joining method, a white tracing method, a geometrical transformation
method and others.
According to the teachings of the present invention, an original image
(i.e. image to be inputted) can be inputted by using an image input device
having an input surface area smaller than the size of the original image
by virtue of such arrangement that the original image is divided into a
plurality of image portions which are then sequentially inputted, whereon
the inputted image portions are joined together on the image memory. Thus,
it is possible to input for storage a picture or image data of greater
size with an inexpensive image input apparatus equipped with an image
input (reading) device having a smaller input or reading surface area.
Further, because the individual input image portions can be matched in the
position with high accuracy upon joining by making use of the marks, the
original image can be restored with high fidelity without distortions to
be subsequently stored in the image memory.
Besides, by adopting the geometrical transformation method and others which
will be described in detail later on, the image portions can be joined
together continuously and smoothly so that joint between the image
portions makes no appearance at any point of the boundary. Thus, the image
resulting from the joining processing can enjoy high image quality without
presenting any appreciable discontinuity when the image is visually
observed.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows a general arrangement of a system for carrying out the present
invention.,
FIG. 2 is a flow chart for illustrating processing procedure according to
an embodiment of the present invention;
FIG. 3 is a view for illustrating a scheme for dividing an image to be
inputted into two image portions;
FIG. 4 is a view showing, by way of example, specifications of a carrier
sheet which can be employed for imputting an image top be processed in
accordance with an embodiment of the invention;
FIGS. 5A, 5B and 5C are views for illustrating the principle underlying a
mark center detecting method based on a structural analysis;
FIG. 6 is a flow chart for illustrating procedure of detecting the mark
center or centroid by the structural analysis method;
FIGS. 7A, 7B and 7C are views for illustrating the principle underlying a
pattern matching method;
FIG. 8 is a flow chart for illustrating the processings involved in
executing the pattern matching;
FIG. 9 is a view for illustrating a least pixel change line detecting
method;
FIGS. 10A, 10B and 10C are flow charts for illustrating processing steps
involved in carrying out the least pixel change line detection method;
FIG. 11 is a view for illustrating a greatest white line detection method
for joining together divided images;
FIG. 12 is a view for illustrating a method for joining together divided
images by resorting to a white tracing method;
FIG. 13 is a view for illustrating an image joining method based on a
logical sum (ORing) method;
FIG. 14 is a view for illustrating a method for joining together two image
portions through a geometrical transformation,
FIG. 15 is a diagram for illustrating correction of orientation of an input
image portion;
FIG. 16 is a view for illustrating a method of indicating joining reference
points by using a mouse, by way of example;
FIG. 17 is a view showing, by way of example, a method of indicating a
joining position of two image portions joined together; and
FIG. 18 is a view for illustrating, by way of example, a method of
inputting an image of a greater size by dividing the image into four image
portions according to another embodiment of the invention.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
Now, the present invention will be described in detail in conjunction with
exemplary or preferred embodiments thereof by reference to the
accompanying drawings.
FIG. 1 shows, by way of example, a general arrangement of a system for
carrying out the present invention. In the figure, a reference numeral 1
denotes a keyboard for inputting code data representing the coordinates of
positions of images or pictures, joining regions thereof and others. A
numeral 2 denotes a CPU (Central Processing Unit) which serves for
controlling the whole system as well as for expansion processing of black
pixels (picture elements) and detection of the joining position and other
processing for images stored in a memory. A numeral 3 denotes a scanner
for inputting images or pictures to be processed (which scanner may also
be referred to as image input means). A numeral 4 denotes a scanner
controller for controlling the scanner 3. A numeral 5 denotes a display
for conforming the code data inputted through the keyboard 1. A numeral 6
denotes a display controller for controlling the display 5. A numeral 7
denotes coding processor for encoding the image inputted through the
scanner 3. A numeral 8 denotes a decoding (restoration) processor for
decoding the coded data of the input image for restoration thereof. A
numeral 9 denotes a file for storing therein the image data undergone the
join processing. A numeral 10 denotes a file controller for controlling
the input/output operation of the image data to/from the file 9. Finally,
a reference numeral 11 denotes a memory (image storing means) for storing
therein the image data inputted through the scanner 3 as well as tho image
data to be processed and the results of the processing.
Next, referring to FIG. 2, description will be made of a flow of
processings executed according to the teachings of the present invention
incarnated in the instant embodiment on the assumption that an image or
picture is divided into two image portions which are inputted separately
and sequentially and joined together into one image on the memory, as is
illustrated in FIG. 3. Now, referring to FIG. 2, a first image portion is
inputted through the scanner 3 at a step 100, which is then followed by a
step 102 where a joining reference point for the image joining is detected
from the first inputted image portion. As the joining reference point,
there may be utilized a characteristic point detected from a joining
position indicator mark printed on a carrier sheet or a mark added
interactively on the screen of the display 5 by using a mouse, a cursor or
the like. At a step 104, there are performed correction of orientation of
the first inputted image portion by determining the top and the bottom
thereof as well as collection of inclination of the first input image
portion by calculating the angle of inclination thereof on the basis of
the joining reference point extracted at the step 102. However, as the
method of performing correction of orientation or disposition of the input
image, there can be conceived such a method as illustrated in FIG. 15 in
addition to the abovementioned method which is based on the utilization of
the joining reference points. More specifically, referring to FIG. 15, a
partial image 81-1 is cut out from an image 80 of concern, whereon
recognizability ratio of characters which can be recognized on the cut-out
image portion in the non-rotated state is compared with the
recognizability ratio of characters recognizable on a partial image 81-2
which corresponds to the cut-out image portion rotated by 180.degree. When
the recognizability ratio for the partial image rotated by 180.degree. is
found greater than that of the non-rotated partial image as the result of
the abovementioned comparison, the input image is rotated by 180.degree..
At a check step 106, the display 5 is made use of for confirming visually
the input image portion undergone the correction of inclination. When it
is decided as a result of this check step 106 that the image inputting has
to be made again, then execution of the processing step 100 to 106 is
repeated at a step 108. If otherwise, a second image portion is inputted
through with the aid of the scanner 3 at a step 110, whereon the
processings similar to those executed at the steps 110 to 118 is performed
to thereby obtain the second image portion corrected in respect to the
inclination. At a step 120, both the first and second image portions are
standardized (i e. both image portions are aligned in size). At a step
122, an optimal joining position is detected from an overlap region
between the two image portions. At a step 124, a joining processing is
performed such that joint along the boundary between the two image
portions become unnoticeable. At a step 126, the two image portions in the
memory 11 is joined together to one image. At a step 128, the image
resulting from the joining step 126 is displayed for the purpose of visual
check (confirmation of the result of the image joining). In that case,
efficiency of the visual check can be enhanced by making use of joining
position marks 95-1, 95-2, etc. indicating the boundary line between the
first input image portion 93 and the second input image portion 94 on the
display screen 92, as is illustrated in FIG. 17. Further, when high
accuracy is required for the joining processing, a function for magnifying
or enlarging the joint portion upon displaying, as shown at 96 in FIG. 17,
may be incorporated to thereby facilitate the visual check.
Parenthetically, the memory 11 has memory areas 11a and 11b for storing
the image portions as divided and a memory area 11 for storing the image
resulting from the processing for joining together the divided image
portions. The joining processing may be performed in the memory area 11a
or 11b. After the joining processing, the joined image may be stored in
the memory area 11c after deletion of the marks which become no more
necessary.
Upon image inputting operation by using the scanner, there may be utilized
a transparent sheet case or a carrier sheet such as shown in FIG. 4. The
specification of the carrier sheet shown in FIG. 4 is so designed as to
allow a picture or image of A3 size to be inputted by using a scanner of
A4 size. In FIG. 4, a reference numeral 31 denotes a layout sheet and 33
denotes a transparent sheet. An image or picture to be scanned is inserted
between the layout sheet 31 and the transparent sheet 33 with reference to
an insert position standard 34 printed on the layout sheet 31 and fixed in
position through cooperation of the layout sheet 31 and the transparent
sheet 33. In FIG. 4, reference numerals 32-1 and 32-2 denote joining
position indicator marks which are printed on the transparent sheet 33 at
mid positions of the left and right sides thereof, respectively.
Turning to FIG. 3, the image carrier or picture 20 whose image is to be
inputted is placed within the carrier sheet, wherein marks 20-1 and 20-2
lying on the picture 20 to be inputted represent the joining position
indicator marks, respectively. Reference numeral 21 denotes a first image
portion and 22 denotes a second image portion. Further, reference numeral
21-1 denotes a region of the first image portion 21 over which the first
image portion is to overlap the second image portion 22, while numeral
22-1 denotes a region of the second image portion 22 over which the latter
overlaps the first image portion 21. It is to be noted that the regions
21-1 and 22-1 are of a same size. Further, numerals 21-2 and 22-2 denote
those regions of the first and second image portions 21 and 22 over which
both image portions 21 and 22 form no overlap with each other. A reference
numeral 23 denotes a joined image resulting from the joining together of
the first and second image portions 21 and 22. Further, a numeral 23-2
denotes a region of the joined image 23 over which the first and second
image portions 22-1 and 22-2 are overlapped with each other. The region
23-2 is of the same size as the regions 21-1 and 22-1, respectively.
It will now be understood from the above description how the image input
operation can be carried out by making use of the carrier sheet having the
joining position indicator marks printed thereon. At this juncture, it
should be mentioned that the joining position indicator marks are only
required to lie within the regions of the first and second image portions
over which these portions are to be overlapped with each other. For
example, the joining position indicator marks may each be prepared in the
form of an adhesive seal which is affixed to the overlapping region of the
image to be inputted.
Next, referring to FIG. 16, description will be made of a method for
indicating the joining reference points on the display screen through
interactive procedure by using a mouse after the image input operation.
In FIG. 16, a reference numeral 85 denotes an image displayed upon
inputting of the first image portion which is designated by 86-4 in this
figure. Further, reference numerals 86-1 and 86-2 denote marks for
indicating an overlap region. A portion 86-3 of the overlap region is
shown as magnified at 89-1. The user viewing the display moves a mouse
cursor 89-2 to a position within the overlap region which is to be
designated as the joining reference point. After having moved the mouse
cursor to the position to be designated as the reference point for the
joining, a mark affixage operation is performed to thereby attach the
joining position indicator mark 90-1 to the first input image portion
which is being displayed. Although it is assumed in the case of the
illustrated embodiment that the mark attaching operation is effected by
depressing a corresponding mouse button, it can readily be understood that
this procedure can equally be realized by inputting a corresponding
command from the keyboard.
For the second input image portion, operation similar to the abovementioned
is performed to affix a joining position indicator mark 90-2. The joining
position indicator marks affixed through the procedure described above can
be made use of as the reference marks for the joining of the first and
second image portions.
Next, description will be directed to a mark detecting operation which is
destined for detection of the mark position and extraction of a
characteristic point characterizing the mark of which the position has
been detected. For detecting the mark position, rectangles enclosing
interconnected black pixels (e.g. a small circle of black pixels) is
extracted from a region of the image at which the mark is to be detected.
Thereafter, of the rectangles as extracted, the position of the rectangle
having a size corresponding to the mark is detected.
As a method of extracting the characteristic point of the mark of which
position has been detected, there may be mentioned a centroid (center
point) detection method based on a structural analysis and a pattern
matching method, which will be described below.
CENTROID DETECTION BY STRUCTURAL ANALYSIS
The principle underlying the centroid detection method based on the
structural analysis will be described by reference to FIGS. 5A, 5B and 5C.
(1) Within the rectangle 35 cut out, distances Ph(y) and Qh(y) to the
leftmost and rightmost contour segments of the mark as well as distances
Pv(x) and Qv(x) to the topmost and lowermost outline segments of the mark
are determined, respectively, whereon a table listing these distances for
discrete values of x and y, respectively, is prepared. In FIG. 5A, only
the distances Pv(x) and Qv(x) in the y-direction are shown.
(2) Next, the distance curve Pv(x) is inverted and then the distance curve
Qv(x) is shifted in parallel by t, as shown at 36 in FIG. 5B, whereon
difference given by Pv(x) - Qv(x t) is determined. Thereafter, a frequency
distribution 37 is determined. With the term "frequency", it is intended
to mean the number of cases (or number of samples) where the difference
Pv(x) - Qv(x t) assumes a certain value. Thus, when the difference
mentioned above assumes a constant value for most of the discrete values
x, the frequency distribution is given by a distribution curve having a
peak at the constant value mentioned above.
(3) The abovementioned processing (2) is repeated for a range of
-sx.ltoreq.t.ltoreq.sx (range delimited by the rectangle cut out) to
thereby create a frequency distribution map.
(4) The abovementioned processings (2) and (3) are also executed for the
differences Ph(y)-Qh(y+t) to thereby create a corresponding frequency map.
(5) Finally, a point at which the frequency defined above becomes maximum
is determined and defined as the center position or centroid of the mark
of concern.
FIG. 6 is a flow chart for illustrating the centroid detection processing
based on the structural analysis.
Referring to the figure, at a step 150, projections of Pv(x) and Qv(x) in
the vertical direction (y-direction) are determined. At a step 152, on the
basis of the projections in the vertical direction, the x-coordinate at
which the black pixels are at maximum is arithmetically determined. The
coordinate x is set up as a provisional centroid of the mark of concern,
whereon the values of the limits sx are determined with reference to the
coordinate x determined arithmetically. At a step 154, the distances Pv(x)
to the upper contour line segment (or points representing the upper
contour line segment) are detected. Similarly, at a step 156, the
distances Qv(x) to the lower contour line segment (points representing the
lower contour line segment) are detected. At a step 158, the maximum value
w.sub.max of the peak value w of a histogram representing th frequency
distribution and magnitude of the shift t in the x-direction at which the
peak value makes appearance in the histogram are set as initial values. At
a step 160, a positional parameter i is initialized to the limit value of
-sx. At a step 162, the histogram peak value representing the frequency
distribution at the position i is set to be w. At a step 164, it is
decided whether or not the value w is greater than the value w.sub.max.
When the decision step 164 results in "NO" (i.e. w is smaller than
w.sub.max), processings at the steps 170 et seq. are performed. Otherwise,
processings at the steps 166 and 168 are executed. At a step 166,
magnitude of the shift i in the x-direction at which the peak value makes
appearance in the histogram is set to be t.sub.O. At a step 168, the
maximum value w.sub.max of the histogram is replaced by the peak value x
of the histogram at the position i. At a step 170, the value of i is
incremented by one. At a step 172, decision is made as to whether or not
the value of i is greater than that of sx. Unless the value of i is
greater than that of sx, the processing steps 162 to 170 are executed
again. Otherwise, the centroid detection routine comes to an end. Through
the similar procedure, magnitude of the shift s.sub.O at which maximum
frequency in the histogram makes appearance in the y-direction can be
determined. In this manner, the centroid positions c.sub.x and c.sub.y of
the mark can be arithmetically determined on the basis of the shift
magnitudes thd O and s.sub.O in the x- and y-directions at which the
maximum values make appearance in the respective histograms in accordance
with
(c.sub.x, c.sub.y)=(t.sub.O /2, s.sub.O /2).
By utilizing the arithmetically determined centroid coordinates,
processings such as correction of inclination, image overlapping and
others are performed. Pattern matching method
FIG. 7 is a view for illustrating the principle underlying the image
overlapping method which is based on the pattern matching. In the FIGS. a
reference numeral 40 denotes a reference image, and 41 denotes a matching
pattern which is cut out from the reference image 40. For cutting out the
matching pattern 41 from the reference image 40, the result of the mark
position detection is utilized. A numeral 42 denotes a joining position
indicator mark which is assumed to be included in the matching pattern 41
in the case of the illustrated embodiment. A numeral 43 denotes an object
image to be matched, 44 denotes a rectangle to be matched, and 45 denotes
a pattern to be matched which is assumed to be included in the rectangle
44. With the pattern matching now under consideration, it is aimed to
detect from the rectangle 44 a pattern having the highest similarity to
the matching pattern 41 and identify the coordinates of the joining
position indicating mark for the detected pattern as the matching
coordinate position.
FIG. 8 shows a processing flow of the pattern matching. At a step 200, the
maximum value R.sub.MAX of a parameter indicating a degree of similarity
and the matching coordinates (w.sub.x, w.sub.y) are set. At a step 202,
the start position for the matching processing in the y-direction is set
as an initial value. At a step 204, the processing start position in the
x-direction is set as an initial value. At a step 206, the number of black
pixels (number of dots) BB existing in a region is arithmetically
determined which region is defined within the rectangle 44 to be matched
(rectangle to undergo the matching processing) and which has a same size
as the matching pattern 41 having an upper left corner ADA (FIG. 7A) at
the coordinates (x, y) and a vertical side LYA and a horizontal side LXA,
as is shown in FIG. 7C. Next, a logical product of the matching pattern
and the rectangle to undergo the matching processing is determined at a
step 208. Subsequently, at a step 210, the number x of the black pixels
for which matching or coincidence is found in the logical product
resulting from the step 208 is arithmetically determined. At a next step
212, the parameter R which represents the degree of similarity between the
matching pattern and the to-be-matched rectangle and which is given by
R=n.sup.2 /BB is arithmetically determined. At a step 214, decision is
made as to whether or not the parameter R representing the degree of
similarity is greater than the maximum value R.sub.MAX thereof. When this
decision step 214 is affirmative (Y), the processing proceeds to a step
216. If otherwise (N), a processing step 218 is executed. At the step 216,
the maximum value R.sub.MAX of the parameter representing the degree of
similarity is set to the value R, wherein the corresponding x-coordinate
is represented by w.sub.x with the y-coordinate by w.sub.y. At the step
218, the value of x is incremented by one. This means that the matching
pattern 41 is shifted relative to the to-be-matched rectangle 44 in the
direction indicated by an arrow 46 by one dot (or by LXA/M when the side
LXA has a length equivalent to the number M of dots). Every time the value
of x is incremented, the value of the similarity parameter R is
arithmetically determined in the manner described above. At a step 220,
decision is made as to whether or not the processing for one line of the
to-be-matched rectangle 44 has been completed (i.e. whether or not the
matching pattern 41 has been shifted just to the right side of the
to-be-matched rectangle 44). When the processing has not yet been
completed, execution of the processing steps 206 to 218 is repeated. On
the other hand, when the processing has been completed, the value of y is
incremented by one at a step 222, which means that the matching pattern 41
is shifted relative to the to-be-matched rectangle 44 in the downward
direction 47 by one bit (or by LYA/N when the side LYA has a length
equivalent to the number N of dots). Every time the matching pattern 41 is
shifted in the downward direction 47 by one dot, the value of the
parameter R is arithmetically determined. At a step 224, it is checked
whether or not the matching processing for the whole rectangle 44 has been
completed. Unless the matching processing is completed, execution of the
processing steps 204 to 222 is repeated. When it is completed, processing
steps 226 et seq. are executed. Namely, at the step 226, the number of the
black pixels within the matching pattern 41 is arithmetically determined.
This number is represented by AA. At the step 228, the degree of
similarity is calculated by using the value AA and the maximum value
R.sub.MAX of the parameter indicating the degree of similarity in
accordance with
##EQU1##
At a step 230, the coordinates (w.sub.x, w.sub.y) at which the degree of
similarity assumes a maximum value are set as the matching coordinate
position, whereupon the pattern matching processing comes to an end.
In the case of the embodiment described hereinbefore in conjunction with
FIG. 5, a circle is shown as the joining position indicator mark utilized
in the centroid detecting method. However, the invention is never
restricted to the circle, but ellipse or rectangle can equally be
employed. Further, in conjunction with the joining position indicator mark
utilized in the centroid detecting method based on the structural
analysis, it is only required that the outermost contour line of the mark
is of a central point symmetry. Accordingly, there may be used, for
example, a circle in which a design such as an emblem is written. On the
other hand, the joining position indicator mark which is used in the
pattern matching method may be of any geometrical shape or pattern on the
condition that the mark can be identified discriminatively from the
ambient background, no graphic pattern similar to that of the mark is
present in the overlap portion and that the mark can be discriminated from
the periphery thereof.
As a method of detecting an optimal joining position from the image overlap
region, there can be conceived a least pixel change line detection method,
a greatest white line detection method, a white tracing method, a random
joining method and others. In the following, the least pixel change line
detection method, a logical OR (sum) joining method, the white tracing
method and the geometrical transformation method will be described as the
optimal joining position detecting methods. Least pixel change line
detection method
The least pixel change line detection method will be explained by reference
to FIG. 9. In the figure, a reference numeral 50-2 denotes an overlap
region where two images or picture overlap each other. For convenience of
description, it is assumed that six lines exist in the overlap region
50-2. In the case of the illustrated example, the number of times
white/black change occurs in each of the six lines is assumed to be six
for the first line, six for the second line, twelve for the third line and
tens for the fourth to sixth lines, respectively, as can be seen in FIG.
9. Thus, the lines for which the number of the white/black changes is
minimum are the first and the second lines 1 and 2. Further, differences
in the number of the white/black changes between the adjacent lines are
"0", "6", "2", "0" and "0" respectively. Thus, the lines for which the
number of white/black changes and the abovementioned difference are
minimum are the first and second lines. Accordingly, the joining position
is detected as lying between the first and second lines.
FIGS. 10A, 10B and 10C are flow charts for illustrating flows of processing
steps involved in carrying out the least pixel change line detection
method on the assumption that image data are fetched on a byte basis from
the overlap region, whereon white or black dot decision is performed on a
dot basis. By checking the white/black dot changes with the aid of a black
pixel detection flag, the number of times the white/black change occurs is
counted. At a step 250, the number of change points and the least pixel
change line position are initialized. At a step 252, the line position for
the detection processing is set to the start line position (y=0) of the
overlap region. At a step 254, the black pixel detection flag is cleared,
and the number of changes in the pixels is initialized to zero. Further,
the byte for detection processing is initially set at the start position
of the line (x=0). At a step 256, the black pixel detection flag is
checked as to whether it contains "1" or "0". In case the flag is "1",
indicating that the immediately preceding pixel is black, then processing
steps 258 to 262 are executed. On the other hand, when the flag is "0",
indicating that the immediately preceding pixel is white, processing steps
318 et seq. are executed. First, let's consider the case where the black
pixel detection flag is "1".
At the step 258, it is checked whether or not the pixels of the x-th byte
on the y-th line are all white. When the pixels of concern are all white,
the processing proceeds to the steps 260 et seq.. Otherwise, the
processing step 278 and the following are executed. At the step 260, the
number or count of pixel changes is incremented by one. At a step 262, the
black pixel detection flag is cleared to zero.
At the step 278, it is checked whether or not the pixels of the x-th byte
on the y-th line are all black. In case these pixels are all black, the
black pixel detection flag is set to "1" at a step 314. If otherwise, a
processing step 290 and the following are executed for making the
white/black decision on the pixel basis. More specifically, at step 290, a
pixel pointer is initialized. At step 292, decision is made as to whether
the pixel pointed by the pixel pointer is white or black. When the pixel
is white, the black pixel detection flag is cleared to zero at the step
294, and the number of pixel changes is incremented by one at the step
298. On the other hand, in case the pixel is black, the black pixel
detection flag is set to "1" at the step 296. At a step 300, the pixel
pointer is incremented by one, and it is checked at a step 302 whether or
not the processing for all the pixels of the x-th byte on the y-th line
has been completed. If so, subsequent processing steps 264 et seq. are
executed for the succeeding one byte. Unless the processing mentioned
above is yet completed, it is then checked at a step 304 whether or not
the black pixel detection flag is "1". If so, execution of the processing
steps 292 to 302 is repeated. When the black pixel detection flag is "0",
it is checked at a step 306 whether the pixel pointed by the pixel pointer
is white or not. In case it is white the black pixel detection flag is
cleared to "0" at a step 310. On the other hand, when the pixel of concern
is black, the black pixel detection flag is set to "1" at a step 308, and
the number or count of the pixel changes is incremented by one, whereon
execution of the processings at the steps 300 et seq. is resumed.
When it is found at the step 256 that the black pixel detection flag is
"0", the processings at steps 318 and the following are performed
similarly to the processings executed when the black pixel detection flag
is "1".
More specifically, at the step 318, it is checked whether or not the pixels
of the x-th byte on the y-th line are all black. When all the pixels of
concern are black, the number or count of pixel changes is incremented by
one (step 320), and the black pixel detection flag is set to "1" (step
322). If otherwise, the processing steps 324 et seq. are executed.
The processing steps 324 to 350 correspond to the processing steps 278 to
314 by reading with the phrase "black pixel" being replaced by "white
pixel".
At the step 264, the position of the byte to undergo the detection
processing is advanced by one. At th | | |
