Image processing method and system

An image processing system and method for converting an input image having continuous tone regions and binary regions into a binary output image includes a block evaluation system that generates a plurality of characteristic values for each block of the input image, and determines a block attributes for each block based on the plurality of characteristic values. The image processing system and method converts the input image into the binary output image on a block-by-block basis using one of a binary region conversion process or a continuous tone region conversion process, wherein the conversion process for each block is selected based on the determined block attribute. In addition, the image processing system and method corrects the determined block attribute based on the block attributes of each block and other blocks surrounding each block. Further, the image processing system and method detects when state transitions between block attributes of adjacent blocks occur, such that the conversion process selection is further controlled by the detected state transitions, based on either the block attributes for each block and other blocks surrounding each block, or the distribution of black, white, and gray pixels in each block. Finally, in the image processing system and method, the block attribute correction and the state transition detection can be used together.

BACKGROUND OF THE INVENTION 
1. Field of the Invention 
This invention relates to an image processing method and system which 
conduct a density conversion process in order to store in memory, print, 
or display an image, input in multiple density levels, in which characters 
and photographs are intermixed. 
2. Description of Related Art 
Conventionally, with image processing systems such as scanners, photocopy 
machines and facsimile machines which can only output binary images, a 
simple binary conversion process is used on binary regions, such as 
characters, line drawings and the like, in order to make the edges of 
these regions sharp and clear in the binary output image. An error 
diffusion method as a continuous tone conversion process is used on 
continuous tone (i.e., gray-scale) regions, such as photographs, in order 
to generate the plurality of different image density levels or density 
gradations in the binary output image. However, there are a large number 
of documents, such as catalogs and the like, within which binary regions, 
such as characters, line drawings and the like, are intermixed with 
continuous tone regions, such as photographs. In these documents, it is 
necessary to evaluate each region in the document and to conduct the 
appropriate conversion process on each evaluated region to generate the 
binary output image. 
To solve this disadvantage, a method is proposed in Japanese unexamined 
patent publication 58-3374. In this reference, the input image is divided 
into blocks. 
The blocks are evaluated by finding the difference between the maximum 
image density and the minimum image density in each block. In Japanese 
unexamined patent publication 58-115975, another method is used. In this 
reference, the blocks are evaluated by finding the edge density of each 
block. 
However, in these two prior art methods, the region evaluation precision is 
low, because only one characteristic amount is used when evaluating the 
blocks. In addition, another disadvantage is that erroneously evaluated 
regions stand out in the binary output image because no correction method 
for correcting the evaluation erroneously evaluated regions has been 
provided. 
SUMMARY OF THE INVENTION 
This invention thus provides an image processing method and an image 
processing system which conduct a density conversion process on an image 
having intermixed binary and gray-scale regions, in order to store to 
memory, or to print or display the converted image. 
This invention further provides an image processing method and image 
processing system wherein the region evaluation precision is improved by 
using two characteristic amounts, specifically the number of black pixels 
and the maximum density difference. 
This invention also provides an image processing method and image 
processing system wherein the region evaluation precision is further 
improved by correcting the results of the target block or pixel evaluation 
by referring to the results of the target block or pixel evaluation for 
surrounding blocks or pixels following the target block or pixel 
evaluation. 
This invention additionally provides an image processing method and image 
processing system wherein erroneously evaluated portions are prevented 
from standing out in the binary output image by detecting blocks in which 
erroneous evaluations are easily produced and switching the conversion 
method within this block or switching the conversion method based on the 
pixel density of this block relative to the results of the evaluation of 
the surrounding blocks. 
The density conversion process takes the mixed binary and continuous tone 
input image and outputs a binary-only output image suitable for printing, 
displaying or transmitting on binary-only devices, such as a binary 
printer, a monochrome monitor and the like. 
In each of the preferred embodiments, the image processing system and 
method of this invention extract two characteristic amounts for each 
region or block of the multiple density-level input image, namely the 
number of black pixels (or alternately the number of white pixels) and the 
maximum density difference, and evaluate each region to determine whether 
the region is a binary region or a continuous tone region using the two 
characteristic amounts. Therefore, the region evaluation precision is 
increased compared to the prior art region evaluation methods that use 
only one characteristic amount. In addition, both characteristic amounts 
are determined using simple processes, so only a short processing time is 
needed and can be implemented in hardware without difficulty. 
In addition, in some of the preferred embodiments, correction of erroneous 
region evaluations is performed, after the region is evaluated, based on 
the region attributes of surrounding regions, where the regions are formed 
of blocks or individual pixels. These attributes indicate whether a region 
is a binary region or a continuous tone region, with the binary region 
attribute being a logic high signal (hereinafter a "1") and the continuous 
tone region attribute being a logic low signal (hereinafter a "0"), for 
example. Thus, it is possible to further enhance the precision of the 
region evaluation. Further, a pattern matching method or a majority 
determination method is used as the correction method, making it possible 
to obtain sufficient results with a simple hardware structure. 
Furthermore, in other ones of the preferred embodiments, after the region 
evaluation process is complete, the existence or lack of existence of a 
state transition between adjacent regions is detected, wherein a state 
transition occurs when the region attribute changes from binary to 
continuous tone or vice versa. In regions where no state transition 
exists, the binary output signals are generated for binary regions and for 
continuous tone regions for all pixels in each region, based on the region 
evaluation results. In regions where a state transition exists, switching 
between the binary output signals generated by the binary conversion 
process and the continuous tone conversion process for the region having 
the state transition is performed based on either the region attributes of 
the surrounding blocks or the state transition. Therefore, it is possible 
to keep errors from standing out in the binary output image. 
In addition, in some of the preferred embodiments, after the correction of 
erroneous region evaluations has been completed, the attribute of the 
target region is corrected based on the attributes of the surrounding 
region, and then the existence or lack of existence of a state transition 
between adjacent regions is detected. In regions where it is determined 
that no state transition exists, the binary output signals are generated 
by either the binary conversion process or the continuous tone conversion 
process for all pixels in the region based on the region evaluation 
correction results. In regions where a state transition exists, switching 
between the binary output signals generated by the binary conversion 
process and the continuous tone conversion process in the region having 
the state transition is performed based on either the corrected attributes 
of the surrounding regions or the pixel density of the corrected region 
having the state transition. By this means, it is possible to make the 
binary output image cleaner. 
One embodiment of the preferred binary output image signal switching method 
of this invention comprises a characteristic amount extraction process 
that extracts a plurality of characteristic amounts contained in the input 
image; a region evaluation process that evaluates each region as one of a 
binary region or a continuous tone region based on the plurality of 
characteristic amounts extracted by the characteristic amount extraction 
process; and a signal selection process that, based on the evaluation 
results of the region evaluation process, outputs a binary output image 
signal converted from the input image by either the binary conversion 
process or the continuous tone conversion process. 
Another embodiment of the preferred image signal switching method of this 
invention comprises a characteristic amount extraction process that 
extracts a plurality of characteristic amounts contained in the input 
image; a region evaluation process that evaluates each region as one of a 
binary region or a continuous tone region based on the plurality of 
characteristic amounts extracted by the characteristic amount extraction 
process; and a signal selection process that, based on the evaluation 
results of the region evaluation process, detects whether or not certain 
blocks of pixels in the input image are in a state of transition between 
the binary region and the continuous tone region relative to surrounding 
blocks, outputs a binary output image signal converted from the input 
image by either the binary conversion process or the continuous tone 
conversion process based on the evaluation results of the region 
evaluation process relative to all pixels in the specific block when no 
such state transition exists, and switches between the binary conversion 
process and the continuous tone conversion process based on the state 
transition in the specific block when such a state transition exists. 
Yet another embodiment of the preferred image signal switching method of 
this invention comprises a characteristic amount extraction process that 
extracts a plurality of characteristic amounts contained in the input 
image; a region evaluation process that evaluates each region as one of a 
binary region or a continuous tone region based on the plurality of 
characteristic amounts extracted by the characteristic amount extraction 
process; and a region evaluation correction process that corrects the 
evaluation results of the region evaluation process. 
One preferred embodiment of the image processing system of this invention 
comprises a density conversion means for converting the density of the 
multiple density level input image, a characteristic amount extraction 
means for extracting a plurality of characteristic amounts contained by 
the input image, a region evaluation means for evaluating each region as 
one of the binary region or the continuous tone region on the basis of the 
plurality of characteristic amounts extracted by the characteristic amount 
extraction means, and a signal selection means for switching between 
binary output image signals generated by either the binary conversion 
process or the continuous tone conversion process based on the evaluation 
results of the region evaluation means. 
Another preferred embodiment of the image processing system of this 
invention comprises a density conversion means for converting the density 
of the multiple density level input image, a characteristic amount 
extraction means for extracting a plurality of characteristic amounts 
contained by the input image, a region evaluation means for evaluating 
each region as one of the binary region or the continuous tone region on 
the basis of the plurality of characteristic amounts extracted by the 
characteristic amount extraction means, region evaluation correction means 
for correcting the region evaluation, and a signal selection means for 
switching between binary output image signals generated by either the 
binary conversion process or the continuous tone conversion process based 
on the evaluation results of the region evaluation means. 
Yet another preferred embodiment of the image processing system of this 
invention comprises a density conversion means for converting the density 
of the multiple density level input image, a characteristic amount 
extraction means for extracting a plurality of characteristic amounts 
contained by the input image, a region evaluation means for evaluating 
each region as one of the binary region or the continuous tone region on 
the basis of the plurality of characteristic amounts extracted by the 
characteristic amount extraction means, state transition detecting means 
for detecting, based on the evaluation results of the region evaluation 
process, whether or not certain blocks of pixels in the input image are in 
a state of transition between the binary region and the continuous tone 
region relative to surrounding blocks, and a signal selection means for 
selectively switching between the binary conversion process and the 
continuous tone conversion process based on the evaluation results of the 
region evaluation process relative to all pixels in the specific block 
when no such state transition is detected by the detection means, and for 
selectively switching between the binary conversion process and the 
continuous tone conversion process based on the state transition in the 
specific block when such a state transition exists. 
These and other features and advantages of the invention are described in 
or apparent from the following detailed description of the preferred 
embodiments.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
In the following preferred embodiments, the input images have both binary 
image portions, such as characters or line art, and continuous tone 
portions, such as photographs. In the input images, the input image 
signals have 256 different density levels (0-255), where white is 
indicated by a density value of 255 and black is indicated by a density 
value of 0. In the output images, the binary output signals have density 
levels of either 0 or 1, where white is indicated by a density value of 1 
and black is indicated by a density value of 0. 
As shown in FIG. 1, the image processing system 100 of this invention 
comprises an image signal switching subsystem 100A and a density 
conversion subsystem 100B. The image signal switching subsystem 100A 
includes a region evaluation subsystem 101 and a signal selection 
subsystem 102. The density conversion subsystem 100B comprises a 
continuous tone image processing subsystem 103 and a binary image 
processing subsystem 104. As shown in FIG. 1, the image signal for the 
mixed continuous tone/binary image is input on signal line 107 
simultaneously to the region evaluation subsystem 101, the continuous tone 
image process subsystem 103 and the binary image processing subsystem 104. 
The region evaluation subsystem 101 evaluates whether the current portion 
of the mixed continuous tone/binary input image is a binary region, such 
as characters, diagrams and other line art, or is a continuous tone 
region, such as photographs and half-tone dots. The results of the 
evaluation are output by the region evaluation subsystem 101 to the signal 
selection subsystem 102. The signal selection subsystem 102 selects which 
one of the binary signals output by the continuous tone image processing 
subsystem 103 and the binary image processing system 104 to output on the 
signal line 106, based on the evaluation results output by the region 
evaluation subsystem. The signal line 106 is connected to one or more of a 
storage system, a communication system, a display, or a printer (not 
shown). 
In addition, the region evaluation subsystem 101 further analyzes half-tone 
regions to determine whether they should be evaluated as a binary region 
or a continuous tone region. This evaluation is based on the number of 
half-tone lines in the half-tone region. For example, in a preferred 
implementation, when the resolution of the mixed continuous tone/binary 
mixed input image is 300 dots per inch (dpi), a half-tone region having 
over 100 lines per inch is evaluated as a continuous tone region, while a 
half-tone region with 100 lines or less per inch is evaluated as a binary 
region. In addition, if the resolution of the input image is 200 dpi, a 
half-tone region having over 50 lines per inch is evaluated as a 
continuous tone region, while a half-tone region having 50 lines or less 
per inch is evaluated as a binary region. 
As described above, the current input image portion input on signal line 
107 is simultaneously input to the continuous tone image processing 
subsystem 103 and the binary image processing subsystem 104 of the density 
conversion system 100B. The continuous tone image processing subsystem 103 
converts the current portion of the mixed continuous tone/binary input 
image into a binary output image portion to be output on the signal line 
106 using a continuous-tone-to-binary conversion method that is 
appropriate for continuous tone regions (hereinafter "the continuous tone 
conversion process"). Similarly, the binary image processing subsystem 104 
converts the current portion of the mixed continuous tone/binary input 
image into a binary output image portion to be output on the signal line 
106 using a binary-to-binary conversion method that is appropriate for 
binary regions (hereinafter "the binary conversion process"). 
It should be appreciated that both the continuous tone image processing 
subsystem 103 and the binary image processing subsystem 104 convert the 
current portion of the input image each time. Accordingly, for one of the 
continuous tone image processing subsystem 103 or the binary image 
processing subsystem 104, the applied conversion method is inappropriate 
for the current portion of the input image, while the other conversion 
method is appropriate for the current portion of the input image. The 
appropriately converted output image is output on the signal line 106 by 
appropriate control of the switch 108 by the signal selection subsystem 
102. That is, the converted output image signal created by either the 
continuous tone image processing subsystem 103 or the binary image 
processing subsystem 104 is selected and output on the signal line 106 by 
the signal selection subsystem 102 controlling the switch 108. 
In the image processing system 100 shown in FIG. 1, the continuous tone 
image processing subsystem 103 and the binary image processing subsystem 
104 operate in parallel. One of the output image signals is selected based 
on the evaluation results from the region evaluation subsystem 101. It 
would also be appropriate to perform the region evaluation process first 
and selectively perform only the appropriate one of the continuous tone 
processing or the binary processing based on the evaluation results. In 
this case, the signal selection subsystem 102 would directly control the 
operation of the continuous tone image processing subsystem 103 and the 
binary image processing subsystem 104, rather than controlling the switch 
108, which would then generally not be needed. 
As shown in FIG. 2, an image signal having both continuous tone portions 
(or regions) and binary portions (or regions) is input to an image input 
system 110, for example, by an image receiving system 201, such as a 
facsimile, a modem, or a network port, or by an image reading system 202, 
such as a scanner. The signal read from the image reading system 202 is 
first converted from analog to digital form. The digital signal output by 
the image reading system 202 is then input to a preprocessing system 203 
that pre-processes the digital signal to perform shading correction on the 
image signal. The preprocessed image signal is then output by the 
preprocessing system 203 to the image input system 110. The image input 
system 110 then distributes the input digital signal to the region 
evaluation subsystem 101, the continuous tone image processing subsystem 
103 and the binary image processing subsystem 104. 
The region evaluation subsystem 101 evaluates whether particular regions of 
the input image are binary regions, such as characters or drawings, or are 
continuous tone regions, such as photographs or half-tone dots. The signal 
selection subsystem 102 selects which converted binary signal, either from 
the binary image processing subsystem 104 or from the continuous tone 
image processing subsystem 103, to output based on the region evaluation 
results for each particular region. 
The continuous tone image processing subsystem 103 converts each region of 
the input image into a binary output image using the continuous tone 
conversion process, which is appropriate for the continuous tone region of 
the input image. The binary image processing subsystem 104 converts each 
region of the input image into a binary output image using the binary 
conversion process, which is appropriate for the binary regions of the 
input image. 
Furthermore, one of the binary images created by the continuous tone image 
processing subsystem 103 and the binary image processing subsystem 104 is 
selected by the signal selection subsystem 102 and is output to the signal 
output means 105. The binary output image signal is output from the signal 
output means 105 to communication circuits or a memory via an image output 
means 204, to an image display system 205, such as a CRT, or to an image 
printing system 206, such as a printer. 
In the image processing system 100 shown in FIG. 2, the region evaluation 
subsystem 101, the continuous tone image processing subsystem 103, and the 
binary image processing subsystem 104 are positioned so that the 
continuous tone conversion process and the binary conversion process are 
performed in parallel, with one of the converted binary output signals 
being selected and output based on the results of the region evaluation 
process. 
FIG. 3 is a flowchart outlining a first preferred embodiment of the region 
evaluation process S101. First, in step S201, a mixed continuous tone and 
binary image, in which the binary and continuous tone regions are 
intermixed, is input. Next, in step S202, the input image is divided into 
blocks which are M pixels wide and N pixels high, where M and N are 
positive integers. Then, in step S203, density conversion of the input 
image signal is performed on a pixel-by-pixel basis. Next, in step S204, 
the number of black pixels is counted for each block, while at the same 
time, in step S205, the maximum density difference is determined for each 
block. Then, in step S206, for each block, an evaluation is performed to 
determine whether the block, if the evaluation is done on a block-by-block 
basis, or the center pixel (target pixel) in each block, if the evaluation 
is done on a pixel-by-pixel basis, is a binary region or a continuous tone 
region. 
Next, in step S207, a binary signal to be output is selected based on the 
results of the evaluation step S206 for each block. Thus, when processing 
each block, when the block is evaluated as a binary region, a switching 
signal is output to select the binary output signal corresponding to the 
binary conversion process for all pixels in the block when the evaluation 
is performed on a block-by-block basis, or for the center pixel when the 
evaluation is performed on a pixel-by-pixel basis. In contrast, when the 
block is evaluated as a continuous tone region, a switching signal is 
output to select the binary output signal corresponding to the continuous 
tone conversion process for all pixels in the block when the evaluation is 
performed on a block-by-block basis, or for the center pixel when the 
evaluation is performed on a pixel-by-pixel basis. 
That is, when the evaluation is performed on a pixel-by-pixel basis, a 
switching signal is output for each pixel to select the binary output 
signal corresponding to either the binary conversion process or the 
continuous tone conversion process. Thus, it should be appreciated that 
the method for dividing the blocks in step S202 differs when the region 
evaluation of step S206 is performed on a block-by-block basis as when the 
region evaluation of step S206 is performed on a pixel-by-pixel basis. 
FIG. 4A illustrates the block evaluation method when the evaluation is 
performed on a block-by-block basis. In this case, the input image is 
divided simply into blocks which are M pixels wide and N pixels high. In 
FIG. 4A, M=5 and N=3. The block of M.times.N pixels is referred to as the 
target block. The evaluation process is performed on each current block 
301, making the block adjacent to it the next target block 302. 
FIG. 4B illustrates the block evaluation method when the evaluation process 
is performed on a pixel-by-pixel basis. In this case, a block is again M 
pixels wide and N pixels high. In FIG. 4B, as in FIG. 4A, M=5 and N=3. The 
block is centered around a target pixel 303. When the next pixel 304 is 
processed, a new block (not shown), which is also M pixels wide and N 
pixels high, is formed and centered around the next pixel 304. 
As described above, the input image signal has 256 possible density levels 
or gradations. Naturally, it is possible to process the signal in the 256 
level form. However, because only 16 density levels are sufficient for the 
region evaluation process of this invention to operate correctly and 
efficiently, the number of density levels in the image signal is 
preferably reduced from 256 to 16. In one preferred embodiment of this 
reduction process, the value of the density level for each pixel is 
divided by 16, and rounded to the nearest integer value. Thus, by 
conducting the density conversion of step S203, the size of the hardware 
can be reduced. It should also be appreciated that either step S202 or 
step S203 can be performed first. 
Preferably, in this invention, the value of N ranges from 1-5 and the value 
of M ranges from 4-20. The value of N is limited only so that the hardware 
requirements for the image memory can be reduced. Thus N can be any value 
supportable by the hardware. The value of M is limited only so that 
instances where both binary and continuous tone regions occur within a 
single block are avoided or minimized. Furthermore, the total number of 
pixels in a block (i.e., the value for (M.multidot.N) is preferably 8-40, 
in order to reduce the amount of calculation and to reduce the size of the 
hardware. During experiments, block dimensions of 16.times.1, 8.times.2, 
10.times.2 and 8.times.3 pixels yielded the best results. 
In step S204, the number of black pixels is the total number of pixels in 
the block having a reduced image density at most equal to the threshold 
value T1. In the first preferred embodiment, T1 is set to 11. The 
inventors have determined during experiments that, in general, the 
threshold value T1 should be set at around 3/4 of the total number of 
input density levels, in order to accurately count the number of black 
pixels without the black pixel count being affected by the background 
color of the paper used in reproduction. Accordingly, in this first 
preferred embodiment, because the number of density levels is set at 16 
through the density conversion step S203, the threshold value is set at 
11, which generally corresponds to 3/4 of 16. 
In step S205, the maximum density difference is the difference between the 
maximum density and the minimum density among the pixels of each block. 
FIGS. 5A and 5B show examples of possible density distributions in a 
block. In FIGS. 5A and 5B, the block is 6 pixels wide and 3 pixels high. 
FIG. 5A shows an example of a binary region, while FIG. 5B shows an 
example of a continuous tone region. In FIG. 5A, the pixels having a 
density of 0 form a portion of a binary image, such as a line or 
character. The pixels having a density of 15 are blank (i.e., white). In 
general, the maximum density difference is large in the binary region 
because the contrast between white and black pixels is distinct. The 
number of black pixels is small because of the large number of blank 
pixels in a binary image. In FIG. 5A, the maximum density difference is 15 
and the number of black pixels, that is, the pixels having a density at 
most equal the threshold value T1 of 11, is 9. 
In contrast, in FIG. 5B, all of the pixels have a density level of either 7 
or 8, as these pixels form a portion of a continuous tone region, such as 
a photograph. In general, the maximum density difference is small in the 
continuous tone region because density changes are gradual. The number of 
black pixels is great because there are few pixels that are white in a 
continuous tone image. In FIG. 5B, the number of black pixels, that is, 
the pixels having a density at most equal to the threshold value T1 of 11, 
is 18, and the maximum density difference is 1. 
In the examples shown in FIGS. 5A and 5B, if the average density is 
determined, the same value would result for both FIG. 5A and FIG. 5B, 
making impossible any distinction between the binary and continuous tone 
regions. However, in this invention, by using the number of black pixels, 
the resulting value differs greatly between the two regions, making it 
possible to distinguish easily between the binary regions and the 
continuous tone regions of the mixed input image. 
It should be appreciated that it would also be appropriate to determine the 
number of white pixels instead of the number of black pixels. The number 
of white pixels is the total number of pixels in a block having an image 
density greater than the threshold value T1. To find the number of black 
pixels from the number of white pixels, the number of white pixels is 
subtracted from the total number of pixels M.multidot.N in the block. When 
this process is performed by hardware, the processes can be performed in 
parallel, as shown in FIGS. 1 and 2. However, when this process is 
performed by software, the processes must be performed serially, with 
either the maximum density difference determining step S205 or the black 
pixel counting step S204 being performed first. 
As described above, after the two characteristic amounts, i.e. the number 
of black pixels and the maximum density difference, have been extracted, 
the evaluation of step S206 to determine whether the target block is a 
binary region or a continuous tone region is performed. 
FIG. 6A illustrates one example of the evaluation conditions used to 
evaluate whether a block, or a pixel, is a binary region or a continuous 
tone region. FIG. 6A shows the region evaluation conditions when the block 
size is 16 pixels by 1 pixel, and the density has 16 gradations 0-15. In 
this case, when both the maximum density difference of a block is at most 
equal to a threshold value T2 and the number of black pixels is at least 
equal to a threshold value T3, the current block falls into area B of FIG. 
6A. Otherwise, if either the maximum density is above the threshold value 
T2 or the number of black pixels is below the threshold value T3, then the 
current block falls into area A of FIG. 6A. When the block falls into area 
B, then the block, if the evaluation is on a block-by-block basis, or the 
center pixel, if the evaluation is on a pixel-by-pixel basis, is evaluated 
as a continuous tone region or pixel. In contrast, when the block falls 
into area A, then the block, or pixel is evaluated as a binary region or 
pixel. For this example, the results of experiments indicate that optimum 
results can be obtained by setting T2=10 and T3=4. 
Another example of the region evaluation conditions is illustrated in FIG. 
6B. In this example, the conditions are not determined by two straight 
lines, one vertical and one horizontal, as in the example shown in FIG. 
6A. Rather, the precision of the evaluation process is enhanced by using 
an inclined line x or a curved line y in place of the perpendicular 
intersection of the horizontal and vertical lines of FIG. 6A. Thus, those 
blocks whose maximum difference values and black pixel values would place 
them in areas C and D, if the inclined line x is used, or area C, if the 
curved line y is used, will be evaluated in FIG. 6B as binary regions 
instead of continuous tone regions. In this invention, the threshold 
values T2 and T3 and the shape of the curve y used in the evaluation 
process are optimized based on the block size used. 
When the number of white pixels is used as a characteristic amount, while 
it may be appropriate to calculate the number of black pixels, but the 
same results can be obtained by replacing the 0 on the horizontal axis 
(number of black pixels) in FIGS. 6A and 6B with 16, and by replacing the 
16 with 0. 
In this way, because the two characteristic amounts (i.e., the number of 
black pixels and the maximum density difference) are used in the region 
evaluation step S206, the precision of the region evaluation process S101 
is enhanced compared to region evaluation methods which use only a single 
characteristic amount. In addition, because each of the characteristic 
amounts can be obtained through a simple process, only a short processing 
time is needed and the hardware implementation can be accomplished without 
difficulty. 
The first preferred embodiments of the specific hardware structures of the 
major subsystems of the image processing device shown in FIGS. 1 and 2 
will be described with reference to FIGS. 7 to 11. FIG. 7 shows the 
structure of the region evaluation means 101 and the signal selection 
means 102 shown in FIG. 2. As shown in FIG. 7, image data stored in an 
image memory 1 is scanned to locate each block of M.times.N pixels. The 
scanned image data is then output on a block-by-block basis to a density 
converter 603, where the density is converted from 256 density levels to 
16 density levels. 
The density converter 603 outputs the block of density-converted image data 
on a pixel-by-pixel basis to a comparator 604. The comparator 604 compares 
the density level of each pixel of the block to the threshold value T1. 
Based on the results of the comparison, the comparator 604 outputs signals 
to a counter 605, which counts 1 each time a black pixel is detected. 
Thus, the total number of black pixels in the block is stored by the 
counter 605. 
The pixel data output from the density converter 603 is also input to a 
maximum value detector 606 and a minimum value detector 607. For each 
block, as each converted pixel is output from the density converter 603, 
the maximum value detector 606 determines if the current pixel has a 
higher density value than the current maximum density value stored in the 
maximum value detector 606, and stores the density value of the current 
pixel if it is higher. Similarly, the minimum value detector determines if 
the density value of the current pixel is lower than the current minimum 
density value stored in the minimum value detector 607, and stores the 
density value of the current pixel if it is lower. The density difference 
is determined as the difference between the density values stored in the 
maximum and minimum value detectors 606 and 607. That is, after the 
current block is completely output by the density converter 603, the 
minimum and maximum value detectors output a minimum value and a maximum 
value for the current block to a differentiator 608. When all pixel data 
in the current block has been scanned, the maximum density difference for 
the current block is output by the differentiator 608. 
In the example shown in FIG. 6A, the value for the number of black pixels 
ranges from 0 to M.multidot.N. which is 18 for the blocks shown in FIGS. 
5A and 5B, and the maximum density difference ranges from 0 to 15. The 
number of black pixels counted by the counter 605 and the maximum 
difference value output by the differentiator 608 are input to a region 
evaluation ROM 609. The region evaluation ROM 609 uses the 5-bit 
number-of-black-pixels value output by the counter 605 and the 4-bit 
maximum-density-difference value output by the differentiator 608 to form 
the 9-bit input address. 
In the region evaluation ROM 609, region evaluation results which use the 
two characteristic amounts as the input addresses are stored as indicated 
in either FIG. 6A or FIG. 6B. Since the region evaluation results are 
stored in the region evaluation ROM 609, rather than being calculated in 
real-time, very complex curves y can be used to divide area A from area B 
without increasing the complexity of the system. From the values for the 
number of black pixels and the maximum density difference, an evaluation 
signal is output from the region evaluation ROM 609 indicating whether 
this block, or the center pixel, is a binary region or a continuous tone 
region. Based on the evaluation signal, a binary output signal, 
corresponding to the block, or the center pixel, and output from either 
the continuous tone image processing subsystem 103 on the signal line 612 
or the binary image processing subsystem 102 on the signal line 613, is 
selected by the binary switching unit 610 to be output on the signal line 
614 to a printer, a display or the like. In FIG. 7, the switching unit 610 
corresponds to the signal selection subsystem 102. 
A first preferred embodiment of the continuous tone image processing 
subsystem 103 shown in FIG. 2 is shown in greater detail in FIG. 8. In 
FIG. 8, the image memory 1 outputs the current block being evaluated by 
the region evaluation subsystem 101 to the continuous tone image 
processing subsystem 103. The current block is input to a gamma correction 
ROM 703 which stores a gamma correction table and which alters the density 
values for the pixels of the current block. The gamma-corrected block is 
output from the gamma correction ROM 703 on a pixel-by-pixel basis and 
undergoes the continuous tone conversion process using the so-called error 
diffusion method. That is, as each pixel of the current block is output to 
the differentiator 704, the density value f for a current pixel is 
corrected by adding to it the weighted error W.sub.ij E.sub.ij, to form 
f'. That is, f'=f+W.sub.ij E.sub.ij. Next, the corrected density value f' 
for the current pixel is compared by a comparator 705 to a binary 
threshold value input on signal line 709. The comparator 705 outputs, 
based on the comparison, a binary valued signal I. That is, based on the 
comparison, I is 0 or 1. The differentiator 706 determines the error 
E.sub.ij, where E.sub.ij =I-f', and stores it in the error memory 707. The 
weighing device 708 performs a weighing process on the error stored in the 
error memory 707 using a weighted matrix W.sub.ij. FIG. 10 shows one 
preferred example of the weighted matrix W.sub.ij. Then, the weighted 
error W.sub.ij E.sub.ij is fed back to the differentiator 704 to be added 
to the gamma corrected density value of a next pixel. 
The gamma correction provided by the gamma correction ROM 703 corrects the 
pixel density based on the attributes of the output device (i.e., the 
printer, the display or the like). That is, when gamma correction is not 
provided, the density information is not correctly evaluated for the 
output device for the continuous tone images. 
FIG. 9 shows one example of the gamma correction curve (for laser printers) 
used in the image processing system 100 of this invention. In FIG. 9, the 
horizontal axis is the input image density level, while the vertical axis 
is the corresponding gamma-corrected image density level. The gamma curve 
used in the present invention has a non-sensitive zone Gb of about 32 
density levels on the black level side and a non-sensitive zone Gw of 
about 64 density levels on the white level side. This gamma correction 
scheme is used to keep errors from standing out in the processed image 
when binary regions are erroneously evaluated as continuous tone regions 
by the region evaluation subsystem 101. When a gamma correction curve such 
as the one shown in FIG. 9 is used, the contrast between white and black 
is distinct and good image quality is obtained, even if part of a 
character erroneously undergoes the continuous tone conversion process to 
generate the binary output. Naturally, when the gamma curve shown in FIG. 
9 is used, the quality of the gray scale in the continuous tone regions 
deteriorates somewhat, but this is not a problem, because, in most every 
actual continuous tone image, there are essentially no image areas that 
are either completely black or completely white. 
FIG. 8 shows a continuous tone image processing subsystem 103 which uses 
the error diffusion method. However, it is also possible for the 
continuous tone image processing subsystem 103 to use a dither method 
which converts the continuous tone regions to the binary output using a 
threshold value which periodically changes. 
FIG. 11 shows a first preferred embodiment of the binary image processing 
subsystem 104 shown in FIG. 2. As shown in FIG. 11, the image memory 1 
outputs the current block being evaluated by the region evaluation 
subsystem 101 to the binary image processing subsystem 104. The block 
output by the image memory 1 is input on a pixel-by-pixel basis to a 
comparator 1004. The comparator 1004 compares a density level of each 
pixel to a binary threshold value input on signal line 1001. Based on the 
comparison, the comparator 1004 outputs a binary output signal. That is, 
based on the comparison, the binary output signal is either 0 or 1. 
In the present example, the threshold value input on signal line 1001 is 
held constant. In particular, the threshold value is set to 128 when there 
are 256 density levels and white is density level 255. However, the binary 
output signal can be created using various well-known methods, such as 
using the average density of the current block as the binary threshold 
value input on signal line 1001. 
FIG. 12 shows a flowchart outlining a second preferred embodiment of the 
region evaluation process. First, after the multi-scale image, in which 
binary and continuous tone regions are intermixed, is input in step S1101, 
in step S1102, the image is divided into blocks which are M pixels wide 
and N pixels high. Next, in step S1103, the input multiple-density-level 
image is density converted. Then, for each block, in step S1104, the 
number of black pixels is counted, while in step S1105, the maximum 
density difference is determined. After the two characteristic amounts, 
which are the number of black pixels and the maximum density difference, 
have been extracted for each block, step S1106 is executed. In step S1106, 
when processing the image on a block-by-block basis, an evaluation is made 
to determine whether each block is a binary region or is a continuous tone 
region. In step S1106, when processing the image on a pixel-by-pixel 
basis, an evaluation is made to determine whether the center pixel in each 
block is a binary region or is a continuous tone region. Thus, steps S1101 
to S1106 of this second preferred embodiment are the same as steps S201 to 
S206 of the first preferred embodiment, so a further detailed description 
of these steps is omitted. 
Following the region evaluation step S1106, step S1107 is executed. In step 
S1107, region correction is performed based on the attributes of the 
target block or the target pixel and the evaluation results of step S1106 
for the surrounding blocks or pixels. In this second preferred embodiment, 
the attribute for the target block or pixel is the binary or continuous 
tone region assigned to the block or pixel resulting from the region 
evaluation on each block or each pixel of step S1106. 
The region correction process of step S1107 is illustrated in FIGS. 13 and 
14. In FIG. 13, the squares labelled 0-8 and A represent blocks or pixels. 
That is, when the region evaluation process of FIG. 12 is performed on a 
block-by-block basis, the squares represent blocks, and when the process 
is performed on a pixel-by-pixel basis, the squares represent pixels. 
Thus, the basic steps in the process are the same, regardless of whether 
the process is accomplished for each block or for each pixel. The 
following description assumes, for ease of illustration, that the process 
is performed on a block-by-block basis. In FIG. 13, the block labelled 0 
is the target block, which is the object of the correction process. Thus, 
blocks 1-8 are reference blocks. 
FIG. 14 shows one preferred example of the attribute patterns used in the 
correction process of step S1107. In FIG. 14, the block indicated by the 
arrow labeled a is the target block, t indicates that the block attribute 
indicates a binary region, p indicates that the block attribute indicates 
a continuous tone region, and * indicates a don't care condition, in that 
the block can be either a binary region or a continuous tone region. 
The block attributes matching the patterns shown in examples A-D of FIG. 14 
are corrected to the patterns indicated by examples A'-D', using only the 
reference blocks present in the row of blocks that is currently being 
processed (i.e. reference blocks 1-5 of FIG. 13). For example, assume a 
region evaluation result matches the pattern shown in example A. In this 
case, only the target block has been evaluated as a continuous tone region 
p, despite the fact that all of the surrounding reference blocks of the 
current row have been evaluated as binary regions t. Therefore, this 
continuous tone evaluation for the target block is considered to be an 
error, and the evaluation is corrected to indicate this block is a binary 
region t, as shown in example A'. The correction patterns A-D correct 
errors in at most two blocks. 
In addition, when using the reference blocks provided in the row of blocks 
currently being processed (reference blocks 1-5) and the row of blocks 
already processed (blocks 6-8), the block attributes matching the patterns 
shown in examples E-J are corrected to the patterns indicated by examples 
E'-J'. In the corrected patterns of examples E'-J', it is possible to 
correct consecutive errors in no more than 3 blocks. 
In this example, attribute correction is accomplished only on the target 
block (the block indicated by the arrow labeled .alpha.. However, when 
blocks matching the pattern in example B, for example, are corrected so 
that one of the two blocks evaluated as continuous tone region p is not 
corrected to be a binary region t, as in example B (as indicated by the 
arrow labeled .beta. in example B), when the target block is shifted one 
block to the right in the next correction pass, this block will be 
corrected because the pattern row now matches example A. Therefore, it is 
not necessary to correct this block in the first pass. The corrected 
patterns are set so as to statistically locate all errors in patterns when 
the region evaluation process is accomplished on various images. 
After the region correction step S1107 has been completed, step S1108 is 
executed. In step S1108, a switching signal is output to select the binary 
output signal corresponding to the attribute of the block. In other words, 
when the block is evaluated to be a binary region, a binary signal 
converted by the binary conversion process is selected and output, and 
when the block is evaluated as being a continuous tone region, a binary 
signal converted by the continuous tone conversion process is selected and 
output. 
In general, when a document image is processed, the process is performed on 
the document from left to right in the first processing direction shown in 
FIG. 13, and is thus accomplished on each line or row of blocks, and after 
processing each line or row of blocks, the system moves to the next line 
or row of blocks in the 2nd processing direction. Accordingly, when region 
correction is performed on the reference blocks shown in FIG. 13, it is 
necessary that the characteristic amount extraction and region evaluation 
processing on at least block 3 of FIG. 13 has been completed. When these 
processes are performed in parallel, the characteristic amount extraction 
and the region evaluation processes are performed on block A, while the 
region correction process is performed on block 0. 
Thus, by correcting the region evaluation of a block or pixel based on the 
attributes of the surrounding blocks or pixels, it is possible to boost 
the precision of the region evaluation process. 
FIG. 15 shows second preferred embodiment of the region evaluation 
subsystem 101 of FIGS. 1 and 2. In FIG. 15, the image memory 1 through the 
region evaluation ROM 609 are the same as in the first preferred 
embodiment shown in FIG. 7. Thus, any further description of these 
elements is omitted. The description which follows will focus on the 
region attribute memory 1401 and the region correction device 1402 of this 
second preferred embodiment. 
The region attribute memory 1401 stores the attributes of the blocks or 
pixels necessary for the region correction process, the memory storing the 
attributes of the row 621 of blocks which are currently being processed 
and the attributes of the row 620 of blocks which have already been 
processed, as shown in FIG. 13. Naturally, when the row 620 of blocks 
which have already been processed is not referred to, it is appropriate to 
store just the attributes of the necessary number of blocks or pixels in 
the row 621 of blocks currently being processed. The region correction 
device 1402 outputs the corrected attribute of the target block or target 
pixel 0 based on the attributes of blocks or pixels 0-8, when the 
reference blocks or reference pixels shown in FIG. 13 are 1-8. The 
attribute of a binary region is 1 and the attribute of a continuous tone 
region is 0. Thus, the target and reference blocks 0-8 provide 9 bits, for 
512 possible input states. For each of the 512 input states, either a 
binary region attribute 1 or a continuous tone region attribute 0 is 
output. The patterns A-J shown in FIG. 14 are included in these 512 
possible states, and when the pattern matches one of these patterns A-J, 
the attribute of the target block or pixel is corrected. 
The output of the region correction device 1402 is input to the binary 
signal switching unit 610 and a binary signal, corresponding to the 
corrected evaluated attribute for the current block or pixel, is output. 
In other words, when processing is performed on each block, a binary 
output signal converted by a binary conversion process is selected when 
the block is a binary region, and a binary output signal converted by a 
continuous tone conversion process is selected when the block is a 
continuous tone region. 
The output of the region correction device 1402 is also fed back to the 
region attribute memory 1401 to overwrite the attribute of the target 
block or target pixel 0. When the input pattern does not match one of the 
patterns A-J shown in FIG. 14, the attributes prior to and after 
overwriting are the same. However, in order to keep the structure of the 
hardware simple, overwriting is always accomplished regardless of whether 
or not the attribute has been corrected. Accordingly, in FIG. 13, the 
region correction process is based on already corrected blocks 4-8, and 
uncorrected blocks 1-3. 
FIG. 16 shows in greater detail a first preferred embodiment of the region 
correction device 1402 and a first preferred embodiment of the region 
attribute memory 1401. In this first preferred embodiment, the region 
correction device 1402 is simply a region correction ROM 1409. As shown, 
in FIG. 16, the region evaluation results for the current block or pixel 
of the current row 621 evaluated by the region evaluation ROM 609 are 
stored in the location indicated by "A" in the region attribute memory 
1401. Furthermore, when the target block or target pixel is 0 and 
reference blocks or reference pixels are blocks or pixels 1-8, signals are 
sent to the region correction ROM 1409 using the attributes of the blocks 
or pixels 0-8 as input addresses for the region correction ROM 1409. The 
region correction ROM 1409 stores a table which outputs the attributes of 
the target block or target pixel 0 based on the pattern formed by the 
attributes of blocks or pixels 0-8 as the input address. When this pattern 
matches one of the patterns A-J shown in FIG. 14, a signal which 
overwrites the attribute of target block 0 is output on signal line 615 to 
the region attribute memory 1401. The overwrite output from the region 
correction ROM 1409 is stored in the target block 0 in the region 
attribute memory 1401. Thus, if the attribute of the target block 0 has 
been, for example, erroneously evaluated as "1", it is overwritten as "0." 
In addition, the output from this region correction ROM 1409 is also used 
as a two-value signal switching signal output on the signal line 611 to 
the binary switching unit 610. Thus, if the output from the region 
correction ROM 1409 is 0, the binary output on the signal line 612 from 
the continuous tone image processing subsystem 103 is selected; while, if 
the output from the region correction ROM 1409 is 1, the binary output on 
the signal line 613 from the binary image processing subsystem 104 is 
selected. 
In FIG. 16, the region correction device 1402 is the region correction ROM 
1409. However, region correction device 1402 is not limited to a region 
correction ROM 1409, and may alternatively be accomplished by a connecting 
circuit, as shown in FIGS. 17 and 18. 
FIG. 17 shows a second preferred embodiment of the region correction device 
1402 of FIG. 15. As shown in FIG. 17, a connecting circuit 1410 
selectively connects the attribute outputs of the target block or pixel 
and the reference blocks or reference pixels retained in the region 
attribute memory 1401 as outlined below. A pattern matching circuit 1404 
determines whether or not the block or pixel attributes of blocks or 
pixels 0-8 match one of the patterns A-J shown in FIG. 14. In the pattern 
matching circuit 1404, one pattern matching circuit device 1404z is 
required for each pattern Z to be matched against. In this embodiment, 
since patterns A-J are used to correct the region evaluation attributes, 
the pattern matching circuit 1404 comprises the pattern matching circuits 
components 1404a-1404j. 
FIG. 18 shows one embodiment for the pattern matching circuit component 
1404a corresponding to pattern A. The connecting circuit 1410 shown in 
FIG. 17 selectively connects the outputs of the target and reference 
blocks or pixels 0-8 to the pattern matching circuit components 
1404a-1404j. Thus, as shown in FIG. 18, the connecting circuit 1410 
connects the attributes of reference blocks 1, 2, 4 and 5 directly to the 
AND gate 1408 of the pattern matching circuit component 1404a. The 
attribute of the target block 0 is connected to the AND gate 1408 via the 
inverter 1407. Therefore, the output of the pattern matching circuit 
component 1404a is 1 only when the input pattern matches pattern A shown 
in FIG. 14. That is, when the attribute of the target block 0 is 0 and the 
attributes of the surrounding reference blocks 1, 2, 4 and 5 are 1, 
pattern A of FIG. 14 is matched. Thus, when these signals are transmitted 
to the pattern matching circuit component 1404a, the output of the pattern 
matching circuit component 1404a is 1. The connecting circuit 1410 
selectively connects the target and reference blocks 0-8 attributes to the 
proper ones of the pattern matching circuit component 1404a-1404j. Since 
the pattern matching circuit components 1404a-1404j correspond to the 
patterns A-J in FIG. 14, the number of inverters 1407 and the insertion 
positions of the circuits varies for each of the pattern matching circuit 
components 1404a-1404j. 
In FIG. 17, the OR gate 1405 outputs the logical OR of the outputs of the 
pattern matching circuit components 1404a-1404j. Thus, when one or more of 
the patterns A-J is matched, the OR gate 1405 outputs a 1. The output of 
the OR gate 1405 and the evaluation attribute of the target block or pixel 
are input to an exclusive OR (XOR) gate 1406 that outputs the exclusive 
logical sum of the output from the OR gate 1405 and the attribute of the 
target block or target pixel 0. Thus, when the output of the OR gate 1405 
is 1, the attribute of the target block or target pixel 0 is reversed. For 
example, if the input pattern matches pattern A, a 1 is output from the 
pattern matching circuit component 1404a and is input to the XOR gate 1406 
via the OR gate 1405. The attribute of the target block or target pixel 0, 
which is 0 because the target block has been erroneously determined to be 
a continuous tone region, is also input to the XOR gate 1406. Thus, a 1 is 
output from the XOR gate 1406 on the signal line 615 and thus is written 
into the region attribute memory 1401 as the corrected attribute of the 
target block or target pixel 0, overwriting the current incorrect target 
block or target pixel attribute of 0. The output from the XOR gate 1406 is 
also transmitted on the signal line 611 to the binary switching unit 610. 
In this second preferred embodiment, the attribute of the target block or 
target pixel is continually updated, but the region correction device 1402 
may be designed such that the attribute is updated only when the output of 
the OR gate 1405 is 1. 
FIGS. 19 and 20 show second preferred embodiments of the continuous tone 
image processing subsystem 103 and the binary image processing subsystem 
104. In general, these second embodiments include the same elements and 
functional connections as the first preference embodiments shown in FIGS. 
8 and 11, respectively. In the second preferred embodiments shown in FIG. 
19 and FIG. 20, the only difference from the first preferred embodiments 
shown in FIGS. 8 and 11 is that a delay circuit 2 is inserted between the 
image memory 1 and the gamma correction ROM 703 of the continuous tone 
image processing subsystem 103 shown in FIG. 19, and between the image 
memory 1 and the comparator 1004 of the binary image processing subsystem 
104 shown in FIG. 20. Most efficiently, the same delay 2 is used to supply 
the delayed block to both the gamma correction ROM 703 and the comparator 
1004. 
Since a 4-block or 4-pixel delay exists between the region evaluation by 
the region evaluation ROM 609 for a block or pixel and the region 
correction by the region correction device 1402 for that same block or 
pixel in the second preferred embodiment of the region evaluation 
subsystem 101 shown in FIG. 15, the delay circuit 2 temporarily stores and 
then synchronizes the image signal read from the image memory 1, so that 
the corresponding binary output signal for that same block or pixel is 
selected only after region correction has been completed on that same 
block or pixel. It is also acceptable to insert a reading regulating 
circuit in place of the delay circuit 2 and to regulate the timing of the 
reading of the image signal from the image memory 1 to synchronize the 
binary outputs of the continuous tone image processing subsystem 103 and 
the binary image processing subsystem 104 with the region evaluation 
subsystem 101. 
An alternate method for the region correcting procedure of step S1107 is 
shown in FIGS. 21A and 21B. The method outlined in FIGS. 21A and 21B is a 
majority determining method which determines the frequency of appearance 
of the attributes in the target block and the reference blocks or the 
target pixel and reference pixels, and selects the most frequently 
appearing attribute as the attribute of the target block or target pixel. 
In FIG. 21A, only the row 621 currently being processed is used to provide 
the reference blocks or pixels. In FIG. 21A, the two blocks or pixels 
positioned before the target block or pixel and the two blocks or pixels 
positioned after the target block or pixel in the current row 621 are used 
as the reference blocks or pixels. The attribute most frequently appearing 
in these five blocks or five pixels is used as the attribute for the 
target block or target pixel. In FIG. 21B, both the row 621 currently 
being processed and the last row 620 just completed are used to provide 
the reference blocks or pixels. In FIG. 21B, the same 5 blocks or pixels 
are used as in FIG. 21A, plus the 5 blocks or pixels in the last row 620 
which are edge-wise adjacent to the 5 blocks or pixels of the current row 
621 are also used as the reference blocks or pixels. Thus, the attribute 
of the majority of the ten blocks or ten pixels is used as the attribute 
of the target block or target pixel. 
The majority determining method has a disadvantage relative to the pattern 
matching method shown in FIGS. 13 and 14, in that, since the attribute 
appearance or pattern is not analyzed, the certainty of the correction 
slightly decreases. However, the majority determination method has an 
advantage, in that the complexity of the procedure does not increase even 
if the number of reference blocks increases. Thus, when the number of 
reference blocks is large, the majority determining method is preferable 
over the pattern matching method. 
FIG. 22 shows a third preferred embodiment of the region correction device 
1402 of FIG. 15. In FIG. 22, the region evaluation ROM 609 and the region 
attribute memory 1401 are the same as shown in FIG. 15. In FIG. 22, the 
region correction device 1402 includes a counter 1901, which reads in the 
attribute for each block or pixel from the region attribute memory 1401 
and determines the number of appearances of either the binary attribute or 
the continuous tone attribute. Thus, for FIGS. 21A and 21B, the calculated 
value ranges from 0-5 or 0-10, respectively, because the number of blocks 
is five or 10, respectively. This determined value is input to a 
comparator 1902, where it is compared with a threshold value input on the 
signal line 618. For FIGS. 21A and 21B the preferred threshold value is 3 
and 6, respectively. The output of the comparator is thus the corrected 
attribute, and is input to the attribute memory 1401 on the signal line 
615. When the determined value of the selected attribute (either binary or 
continuous tone) is greater than the threshold value, the attribute of the 
target block or pixel is set to the selected attribute. When the 
determined value is less than the threshold value, the attribute is taken 
as the non-selected attribute (either continuous tone or binary). The 
output from the comparator 1902 is also output as the selection signal, 
which is transmitted to the binary signal switching unit 610 on the signal 
line 611. 
In the second preferred embodiment of the region evaluation subsystem 101 
shown in FIG. 15 and the method shown in FIG. 12, the region evaluation 
accuracy can be further improved because incorrect region evaluations are 
corrected based on the attributes of the surrounding blocks after it has 
been determined whether or not the region is a binary region or a 
continuous tone region. 
In general, when evaluations are carried out for each block, since 
inappropriately converted binary images end up being output for entire 
blocks which are erroneously evaluated, the errors have a tendency to 
stand out. In particular, when the state changes from a binary region to a 
continuous tone region, or from a continuous tone region to a binary 
region, errors on the transition boundaries stand out. 
In third preferred embodiments of the region evaluation method and 
subsystem 101, blocks in which state transition boundaries exist are 
detected. FIG. 23 shows a flow chart outlining a third preferred 
embodiment, comprising the first preferred embodiment of the region 
evaluation process S101 and a first preferred embodiment of a signal 
selecting process S102. Steps S2001-S2006 are identical to steps S201-S206 
of the first preferred embodiment shown in FIG. 3. Accordingly, a detailed 
description of these steps is omitted. However, step S207 of the first 
preferred embodiment shown in FIG. 3 has been replaced with the signal 
selecting process S102 shown in the third preferred embodiment shown in 
FIG. 23. 
In the signal selecting process S102, in step S2007, the attribute of the 
target block is checked to determine if the state of the evaluation 
attribute, relative to either laterally adjacent block, has changed from 
binary region to continuous tone region, or from continuous tone region to 
binary region, or in other words, whether or not the state has changed. 
If, in step S2007, it is determined that the state has changed, the 
attributes of the surrounding blocks for which the evaluation procedure 
has been completed are compared in step S2008. That is, in step S2008, the 
frequency of appearance of the binary region attribute and the continuous 
tone region attribute among the attributes of the reference blocks and the 
target block are compared. Then, in step S2009, a switching timing is 
generated for the binary output within the target block. In step S2010, 
when a state transition has thus occurred, the selection of the binary 
output signal within the block is changed and the binary output signals 
are selectively output by the switching timing. That is, the output source 
for the output signal for the target block is altered, as the output 
signal is output. In the previous embodiments, once the output source is 
selected for a target block, that source is used for all the pixels of 
that block. In contrast, in this third preferred embodiment, the output 
source selected during the signal selection process S102 is changed for 
some of the pixels of the target block. 
Conversely, if it is determined in step S2007 that no state transition 
exists in the target block, control jumps directly to step S2010, where 
the switching signal is output based on the region evaluation result from 
step S2006. 
FIG. 24 shows a third preferred embodiment of the image processing system 
100, comprising the first preferred embodiment of the region evaluation 
subsystem 101 and a first preferred embodiment of the signal selection 
subsystem 102. In FIG. 24, the image memory 1 through the region 
evaluation ROM 609 are the same as shown in FIG. 7. As in the second 
embodiment shown in FIG. 15, the region evaluation result for the current 
block being evaluated by the region evaluation ROM 609 is stored in area Y 
of the region attribute memory 1401. In the region attribute memory 1401, 
the target block 0 is surrounded by the reference blocks 1-3 and X-Y. 
The signal selecting subsystem 102 includes a state transition detecting 
circuit 2101, an attribute pattern ROM 2102, a timing generator 2103, and 
a switching unit 2104. The state transition detecting circuit 2101 detects 
if the target block attribute has changed, and includes two XOR gates 2105 
and 2106 and an OR gate 2107, which outputs the logical OR of the output 
from the XOR gates 2105 and 2106. The XOR gate 2105 is connected to the 
reference block X and the target block 0 of the region attribute memory 
1401, while the XOR gate 2106 is connected to the reference block 1 and 
the target block 0. The XOR gates 2105 and 2106 each output a 1 only when 
the values are different for the blocks X and 0, and the blocks 1 and 0, 
respectively, which indicates a state transition has occurred. The outputs 
of the XOR gates 2105 and 2106 are connected to the OR gate 2107. The 
output of the OR gate 2107 is input to the control input S1 of the 
switching unit 2104. The attribute signal of each block 0-3 and X-Y is 1 
for the binary region attribute and 0 for the continuous tone region 
attribute. 
The attribute pattern ROM 2102 inputs the attributes of the target block 0 
and the reference blocks 1-3 as input addresses, and outputs patterns 
based on the input attribute values. The timing generator 2103 generates a 
switching signal based on the output of the attribute pattern ROM 2102. 
The switching signal is output to the B input of the switching unit 2104, 
while the attribute value of the target block 0 is output to the A input 
of the switching unit 2104. 
When a state transition has not occurred between either the blocks 1 and 0, 
or between the blocks X and 0, the output of the OR gate 2107 is 0. In 
response to a 0 on the control input S1, the switching unit 2104 selects 
the A input. The switching unit 2104 thus selects and transmits the region 
evaluation result from the region evaluation ROM 609 for the target block 
0 to the signal line 611. When a state transition has occurred between 
either or both of the sets of blocks 0 and 1, or blocks 0 and X, the 
output of the OR gate 2107 is 1. In response to a 1 on the control input 
SI, the switching unit 2104 selects the B input. The switching unit 2104 
thus selects and transmits the switching signal from the timing generator 
2103 to the signal line 611. 
In other words, when a state transition has not occurred, the input A, 
corresponding to the region evaluation result from the region evaluation 
ROM 609 for the target block 0, is connected by the switching unit 2104 to 
the binary signal switching unit 610 by the signal line 611. When a state 
transition has occurred, the input B, generated by the timing generator 
2103 based on the output of the attribute pattern ROM 2102, is connected 
to the binary signal switching unit 610 by the signal line 611. 
FIG. 25 shows the region evaluation results for two rows of blocks 620 and 
621. The region evaluation procedure is completed for row 620, while the 
region evaluation procedure is in process for row 621. In FIG. 25, each 
block comprises 16 pixels in the horizontal row (i.e. M=16) and an 
indeterminant number of rows n. In FIG. 25, t indicates that the entire 
block has been determined to be a binary region block, while p indicates 
that the entire block has been determined to be a continuous tone region 
block. The block indicated by the arrow .alpha. is the target block 0. In 
FIG. 25, the target block 0, which should have been determined to be a 
continuous tone region p, has been erroneously determined to be a binary 
region t. 
When the attributes of the target block and the reference blocks, as shown 
in FIG. 25 by the dotted line and in part (a) of FIG. 26, are transmitted 
to the attribute pattern ROM 2102, the output pattern shown in part (b) of 
FIG. 26 is obtained. That is, in this example, the input to the attribute 
pattern ROM 2102 is the attributes for the four blocks surrounded by the 
dotted line in FIG. 25. Based on the attributes of this 4-block portion, 
since three blocks have been evaluated as being binary regions and only 
one has been evaluated as being a continuous tone region, an output 
pattern of "1110" is obtained from the attribute pattern ROM 2102. This 
output pattern considers the appearance frequency of each attribute and 
the attribute pattern of the block, and is formed so as to preserve 
attribute continuity. 
In FIG. 25, considering the five horizontally aligned units as a single 
block, the second and third blocks from the left are taken as boundaries. 
Thus, the left side of the resulting block, as shown in part (a) of FIG. 
26, is a binary region for characters or the like, and the right side is 
the continuous tone region for a photograph or the like. If, instead, the 
output pattern is taken to be "0111", because, in FIG. 25, the left side 
is a binary region and the right side is a continuous tone region, the 
error stands out noticeably because a continuous tone region exists on the 
left side, and the region no longer matches the surrounding attributes. 
Thus, at this point, the output "1110" is obtained from the attribute 
pattern ROM 2102, as shown in part (b) of FIG. 26. 
The timing generator 2103 which receives this pattern "1110" outputs a 
switching signal to the B input of the switching unit 2104, as shown in 
part (d) of FIG. 26, based on the described pattern "1110", corresponding 
to the 4-pixel blocks of the 16 pixels which form each horizontal row of 
the target block 0, as shown in part (a) of FIG. 26. 
If the output at this point is the same as the region evaluation result 
from the region evaluation ROM 609 input on the input A of the switching 
unit 2104, since the entire block is evaluated as a binary region, a 
switching signal input to the A input (in this case, a 1, indicating a 
binary region, such as is shown in part (c) of FIG. 26), is transmitted 
from the switching unit 2104 to the binary signal switching unit 610 on 
the signal line 611. This target block, which originally should have been 
processed as a continuous tone region, is thus entirely processed as a 
binary region. 
However, an output of "1110" is obtained from the attribute pattern ROM 
2102, as shown in part (b) of FIG. 26. As shown in part (d) of FIG. 26, a 
switching signal input to the B input and corresponding to the pattern 
"1110" is transmitted from the switching unit 2104 to the binary signal 
switching unit 610 on the signal line 611. Thus, since 0, indicating a 
continuous tone region, is transmitted to the binary signal switching unit 
610 for the fourth 4-pixel block of the four 4-pixel blocks formed from 
the 16 pixels forming each row of the target block, or in other words, for 
1/4 of the target block 0, it becomes possible to carry out the correct 
procedure for 1/4 of the target block 0. 
There are many cases in which the error shown in FIG. 25 occurs when the 
block catches on the edge of the photograph region. Even if one portion of 
the block is not correctly output, the binary image output is clean. In 
addition, since blocks for which state transition has occurred do not 
necessarily contain errors, there is a possibility that a mistaken 
procedure will be accomplished for correctly evaluated blocks, but these 
errors will not stand out noticeably in the output binary images. 
The continuous tone image processing subsystem 103 and the binary image 
processing subsystem 104 connected to the first preferred embodiment of 
the region evaluation subsystem 101 and the first preferred embodiment of 
the signal selection subsystem 102 in this third preferred embodiment of 
the image processing system 100 are the same as those shown in FIGS. 19 
and 20. However, since the region evaluation result is written into block 
Y and the binary output is selected for the target block 0, the delay 
interval of the delay circuit 2 is equivalent to a 2-block portion. 
As described above, in this third embodiment of the image processing system 
100 comprising the first preferred embodiment of the region evaluation 
subsystem 101 and the first preferred embodiment of the signal selection 
subsystem 102, a determination is made, based on the maximum density 
difference and the number of black pixels, whether or not the target block 
is a continuous tone region. State transitions of the region attribute are 
then detected between the target blocks and the immediately adjacent 
blocks of the same row. When no state transition exists, the binary output 
is selected based upon the region evaluation result. When a state 
transition exists, the region attributes of the target and surrounding 
blocks are compared, to selectively switch between the two binary output 
signals within the target block. Thus, ultimately, the error of a binary 
image that has been output does not stand out noticeably. 
FIG. 27 outlines a flow chart of a fourth preferred embodiment of the image 
processing system 100, comprising the first preferred embodiment of the 
region evaluation process S101 and a second preferred embodiment of the 
signal selecting procedures S102. Since steps S2401-S2406 are the same as 
steps S201-S206 of the first-third preferred embodiments of the region 
evaluation process S101, a detailed description of these steps is omitted. 
As shown in FIG. 27, in step S102, if, in step S2407, a state transition is 
detected, step S2408 is performed. Otherwise, step S2409 is performed. In 
step S2408, the program determines whether to employ a binary region 
conversion process or a continuous tone conversion process to generate the 
binary output signal. Then, in step S2409, a selected switching signal is 
output, based on the conversion process selected in step S2408 when a 
state transition has occurred, or based on the region evaluation result 
when no state transition has occurred. 
In step S2408, the density of the input pixel signal, after the conversion 
to the 16 level form, is checked to determine if the density is 1 or below 
(black), 13 or above (white), or between 2-12 (grey). If, in step S2408, 
the pixel signal density is 1 or below, or 13 or above, the binary 
conversion process is selected. However, in step S2408, if the density is 
between 2-12, the continuous tone conversion process is selected. 
In FIG. 28, the image memory 1 through the region evaluation ROM 609 are 
the same as in the first preferred embodiment shown in FIG. 7. The region 
evaluation result for the current block Y from the region evaluation ROM 
609 is stored in the region attribute memory 1401. 
The signal selection subsystem 102 includes the state transition detecting 
circuit 2101, an output procedure selecting circuit 2501, and the 
switching unit 2104. The output procedure selecting circuit 2501 includes 
two comparators 2502 and 2503 and an OR gate 2504. The output procedure 
selecting circuit 2501 transmits a "1" to the B input of the switching 
unit 2104 when the density of each pixel of the target block 0 is 1 or 
below (black) or 13 or above (white), and transmits a 0 to the B input of 
the switching unit 2104 if the density of each pixel is between 2-12 
(grey). 
When a state transition has not occurred, the described switching unit 2104 
selects and transmits the region attribute of the target block 0 which 
corresponds to the region evaluation result from the region evaluation ROM 
609. When a state transition has occurred, the switching unit 2104 selects 
and transmits the output of the output procedure selecting circuit 2501, 
which is input on the B input. In other words, when a state transition has 
not occurred, the region evaluation result from the region evaluation ROM 
609 is transmitted by the switching unit 2104 to the binary signal 
switching unit 610 on the signal line 611. When a state transition has 
occurred, the output of the output procedure selecting circuit 2501 is 
transmitted to the binary signal switching unit 610 on the signal line 
611. The binary signal switching unit 610 operates as described in the 
first preferred embodiment shown in FIG. 7. 
As shown in FIG. 29, the block size is 16 pixels in each row, with the 
number of rows n is indeterminate. The density of the three pixel block Z 
is 2-4, and the density of the other 12 pixels is 14. In such a state, the 
block appears in the state in which it has caught on the edge portion of 
the intermediate tone region. In this case, since the number of black 
pixels is 3 and the maximum density difference is 12, the block which 
should have been evaluated as a continuous tone region is erroneously 
evaluated as a binary region. 
When the pixel signal of the type of the target block 0 shown in part (a) 
of FIG. 29 is input to the output procedure selection circuit 2501, a 
binary conversion processing selection signal (=1) is output from the 
output procedure selection circuit 2501, as shown in part (c) of FIG. 29, 
for those pixels having a density 14, while, for those pixels having a 
density 2-4, a continuous tone processing selection signal (=0) is output. 
Conversely, if the output is to be the same as the region evaluation 
result based on the results of the state transition detection device 2101, 
the region evaluation result (=1) input to the A input of the switching 
unit 2104 is output, as shown in part (b) of FIG. 29. 
However, when the fourth preferred embodiment of the method is used, the 
correct procedure can be accomplished for the correct binary output based 
on the continuous tone portion. Since blocks for which a state transition 
has occurred do not necessarily contain errors, there is a possibility of 
selecting the wrong binary conversion procedure for correctly evaluated 
blocks. However, since the binary conversion procedure is selected based 
on the pixel density, the errors do not stand out in the output binary 
image. 
The continuous tone image processing subsystem 103 and the binary image 
processing subsystem 104 connected to the first preferred embodiment of 
the region evaluation subsystem 101 and the second preferred embodiment of 
the signal selection subsystem 102 in this fourth preferred embodiment of 
the image processing system 100 are the same as those shown in FIGS. 19 
and 20. However, since the region evaluation result is written into block 
Y and the binary output is selected for the target block 0, the delay 
interval of the delay circuit 2 is equivalent to a 2-block portion. 
As described above, in this fourth preferred embodiment of the image 
processing system 100 comprising the first preferred embodiment of the 
region evaluation subsystem 101 and the first preferred embodiment of the 
signal selection subsystem 102, a determination is made, based on the 
maximum density difference and the number of black pixels, whether or not 
the target block is a continuous tone region. State transitions of the 
region attribute are then detected between the target blocks and the 
immediately adjacent blocks of the same row. When no state transition 
exists, the binary output is selected based upon the region evaluation 
result. When a state transition exists, the region attributes of the 
target and surrounding blocks are compared, to selectively switch between 
the two binary output signals within the target block. Thus, ultimately, 
the error of a binary image that has been output does not stand out 
noticeably. 
FIG. 30 shows a flow chart outlining a fifth preferred embodiment for the 
image processing method, comprising the second preferred embodiment of the 
region evaluation process S101 and the first preferred embodiment of the 
signal selection process S102. Accordingly, as these processes are fully 
described with reference to FIGS. 12 and 23, any further discussion of 
these steps is omitted. 
A fifth preferred embodiment of the image processing system 100 is shown in 
FIG. 31, and generally comprises the second preferred embodiment of the 
region evaluation subsystem 101 shown in FIG. 16 connected to the first 
preferred embodiment of the signal selection subsystem 102 shown in FIG. 
24. Accordingly, since these subsystems and devices are fully described 
above, except as set forth below, any further discussion of these 
subsystems and devices is omitted. 
As shown in FIG. 31, while the attribute pattern ROM 2102 and the state 
transition detecting device 2101 are connected to blocks of the region 
attribute memory 1401, the connected blocks differ from that of the third 
preferred embodiment shown in FIG. 24. That is, because the region 
correction ROM 1402 corrects the target block 0, the target block 0 is not 
stable. Thus, instead of using the target block 0 and its surrounding 
blocks 1-3 and X, as in the third preferred embodiment shown in FIG. 24, 
the state transition detecting device 2101 is connected to the blocks 4, 5 
and X, which are all stable. Likewise, the attribute pattern ROM 2102 is 
connected to blocks 4 and X-Z, which are also all stable. Thus, the signal 
selection subsystem 102 outputs the selection signal to the binary signal 
switching unit 610 corresponding to block 4 while block 0 is corrected by 
the region correction ROM 1402. 
It should be appreciated that either the second preferred embodiment of the 
region correction device 1402 shown in FIG. 17 or the third preferred 
embodiment of the region correction device 1402 shown in FIG. 22 can be 
used in place of the first preferred embodiment of the region correction 
device 1402 used in FIG. 31. However, in the fifth preferred embodiment 
shown in FIG. 31, since the region evaluation result is written into block 
"A" and the appropriate binary output is selected for block "4," the delay 
interval in the delay circuit 2 shown in FIGS. 19 and 20 corresponds to a 
6-block portion delay interval. 
Since multiple characteristic amounts are extracted from the multi-scaled 
input images and binary and continuous tone evaluations are performed from 
these multiple characteristic amounts, region evaluations are possible 
that are much more accurate than conventional region evaluation methods 
that do not use more than one characteristic amount. By transmitting 
binary converted image signals or continuous tone converted image signals 
according to the region evaluation results, optimum image processing can 
be accomplished for each region. 
In addition, after regions are evaluated, if there are errors in the 
evaluated results, the errors of the evaluated results can be corrected by 
comparing the erroneously evaluated portions with the surrounding region 
attributes, thus making faster region divisions possible. 
Furthermore, after regions are evaluated, a determination is made as to 
whether or not state transitions have occurred in the blocks. If state 
transitions have occurred, switching between binary conversion and 
continuous tone conversion is performed within those blocks based on the 
state transitions. Thus, in blocks for which state transitions have 
occurred, the entire blocks are not evaluated simply as either binary 
regions or continuous tone regions, but can instead switch between being 
treated as binary regions and continuous tone regions within the blocks 
based on the state transitions. Therefore, errors in the binary images 
which are ultimately output need not stand out noticeably. Moreover, the 
attribute correction and state transition detection methods and devices 
can be combined to obtain both advantages simultaneously. 
FIG. 32 shows a flow chart outlining a sixth preferred embodiment for the 
image processing method, comprising the second preferred embodiment of the 
region evaluation process S101 and the second preferred embodiment of the 
signal selection process S102. Accordingly, as these processes are fully 
described with reference to FIGS. 12 and 27, any further discussion of 
these steps is omitted. 
A sixth preferred embodiment of the image processing apparatus 100 is shown 
in FIG. 33, and generally comprises the second preferred embodiment of the 
region evaluation subsystem 101 shown in FIG. 16 connected to the second 
preferred embodiment of the signal selection subsystem 102 shown in FIG. 
28. Accordingly, since these subsystems and devices are fully described 
above, except as set forth below, any further discussion of these 
subsystems and devices is omitted. 
As shown in FIG. 33, while the attribute pattern ROM 2102 and the state 
transition detecting device 2101 are connected to blocks of the region 
attribute memory 1401, the connected blocks differ from that of the fourth 
preferred embodiment shown in FIG. 28. That is, because the region 
correction ROM 1402 corrects the target block 0, the target block 0 is not 
stable. Thus, instead of using the target block 0 and its surrounding 
blocks 1-3 and X, as in the fourth preferred embodiment shown in FIG. 28, 
the state transition detecting device 2101 is connected to the blocks 4, 5 
and X, which are all stable. Likewise, the output procedure selecting 
circuit 2501 is connected to block 4, which is stable. Thus, the signal 
selection subsystem 102 outputs the selection signal to the binary signal 
switching unit 610 corresponding to block 4 while block 0 is corrected by 
the region correction ROM 1402. 
It should be appreciated that either the second preferred embodiment of the 
region correction device 1402 shown in FIG. 17 or the third preferred 
embodiment of the region correction device 1402 shown in FIG. 22 can be 
used in place of the first preferred embodiment of the region correction 
device used in FIG. 33. However, in the sixth preferred embodiment shown 
in FIG. 33, since the region evaluation result is written into block "A" 
and the appropriate binary output is selected for block "4," the delay 
interval in the delay circuit 2 shown in FIGS. 19 and 20 corresponds to a 
6-block portion delay interval. 
Since multiple characteristic amounts are extracted from the multi-scaled 
input images and binary and continuous tone evaluations are performed from 
these multiple characteristic amounts, region evaluations are possible 
that are much more accurate than conventional region evaluation methods 
that do not use more than one characteristic amount. By transmitting 
binary converted image signals or continuous tone converted image signals 
according to the region evaluation results, optimum image processing can 
be accomplished for each region. 
In addition, after regions are evaluated, if there are errors in the 
evaluated results, the errors of the evaluated results can be corrected by 
comparing the erroneously evaluated portions with the surrounding region 
attributes, thus making faster region divisions possible. 
Furthermore, after regions are evaluated, a determination is made as to 
whether or not state transitions have occurred in the blocks. If state 
transitions have occurred, switching between binary conversion and 
continuous tone conversion is performed within those blocks based on the 
state transitions. Thus, in blocks for which state transitions have 
occurred, the entire blocks are not evaluated simply as either binary 
regions or continuous tone regions, but can instead switch between being 
treated as binary regions and continuous tone regions within the blocks 
based on the state transitions. Therefore, errors in the binary images 
which are ultimately output need not stand out noticeably. Moreover, the 
attribute correction and state transition detection methods and devices 
can be combined to obtain both advantages simultaneously. 
While this invention has been described in conjunction with specific 
embodiments thereof, it is evident that many alternatives, modifications 
and variations will be apparent to those skilled in the art. Accordingly, 
the preferred embodiments of the invention as set forth herein are 
intended to be illustrative, not limiting. Various changes may be made 
without departing from the spirit and scope of the invention as defined in 
the following claims.