JPH0316468A - Picture processing unit - Google Patents

Abstract

PURPOSE:To execute the picture processing with high quality suitable for respective picture by selecting and outputting the result of the multi-value processing emphasizing white and black levels when a picture is discriminated to be a character picture and the result of the multi-value processing emphasizing also intermediate gradation when a picture is discriminated to be a gradation picture. CONSTITUTION:An optical image obtained by scanning an object (original) 1 optically is led to a picture read section 3 via a lens system 2, converted into an electric signal (picture signal) and converted into a digital picture signal in a prescribed bit by an A/D converter 4. The digital picture signal is subjected to correction of resolution by an MTF correction at a resolution correction section 7, fed to a gradation picture processing section 8 and different picture processing from a character picture and a gradation picture is executed, The data is fed to a character picture processing section 20 acting like a multi-value processing means, in which the picture processing specific to the character picture to reproduce the character sharply is implemented. Moreover, the picture is fed to an intermediate tone processing section 21 acting like the multi-value processing means via a low pass filter 31 of a mixed picture discrimination means 50 to provide prescribed gradation characteristic.

Description

DETAILED DESCRIPTION OF THE INVENTION (Field of Industrial Application) The present invention relates to an image processing device suitable for a digital copying machine, and more specifically, to an image processing device suitable for a digital copying machine. It relates to a processing device.

(Background of the fourth issue) In general, in electrophotographic digital copying machines,
The image information (original image) of the original is divided into micropixels of approximately several tens of microns, the electric signal (image signal) corresponding to the density of each pixel is converted into a digital signal, and the digital image signal is processed internally. After conversion, the image is output to a storage device such as a laser, and a copy image is obtained through an electrophotographic process.

In such digital copying apparatuses, internal signal processing is often changed depending on the type of manually generated image.

For example, when the input image is a so-called general document such as a book or a letter, the density of the characters and the color level of the background are not so important, and it is desired that the characters be reproduced sharply.

Therefore, in the case of a printer that has only two output values (on and off), the input image information is set to a certain fixed level (threshold value).
The image is reproduced by binarizing it.

In the case of a printer capable of multi-value recording according to density, character images can be reproduced clearly by controlling the reproduction with emphasis on white and black output.

On the other hand, when the input image has so-called gradation, such as a photographic image, reproduction of intermediate tones becomes important, which is different from when the purpose of processing is mainly text.

For example, in the case of a binary printer, a pseudo halftone image is formed using a well-known method such as a dither method or a density matrix method, and the image is reproduced using the output. Even in the case of multilevel printers, the output characteristics are often designed to emphasize the reproduction of halftones.

Furthermore, especially in these processes, halftone drawings often used in newspapers and the like require special processing. Halftone drawings are made up of many dots, and when viewed microscopically, they do not have any mid-tone areas and are similar to character drawings.

However, since the original purpose of halftone drawings is to reproduce pseudo-halftones using dots of different sizes, it is often easier to see the output if it is reproduced as a gradation image similar to that of a photographic image. Furthermore, a certain number of lines among halftone dots is very close to the sampling pitch used in the image reading system and writing system of digital copying devices that are currently widely used.

For example, when the sampling pitch is 16 dat/mm and the number of mesh lines is 133 lines/inch, the number of mesh lines is quite close to the sampling pitch.

Under such conditions, an aliasing error occurs in sampling, which appears as a so-called moiré image, resulting in a significant deterioration in image quality. Moiré appears particularly clearly when the original image is binarized, but even when pseudo-intermediate representation such as dithering is applied, the frequency of appearance only decreases and it does not disappear completely.

As a countermeasure to this problem, it is possible to reduce the high frequency components of the original image to reduce interference with the sampling pitch. Specifically, it is sufficient to perform smoothing using surrounding pixels.

As described above, by switching the coefficients for image processing and multi-value conversion according to the characteristics of each image, the output image can be maintained in high quality. Normally, these switching is performed by the operator himself by switching the processing mode depending on the document.

However, when copying a document such as a pamphlet that has different features such as text and photos in one image,
If text and image processing is set, the reproducibility of photographic parts will be lost, making it impossible to obtain a copy that is satisfactory for both parties. Therefore, the overall copy quality is not good.

To solve this problem, it is necessary to determine whether the human image information is a character image or a gradation image. The process may be switched based on the i++-specific results.

Conventionally, the so-called block-by-block discrimination method, which divides the original image into several small blocks and switches processing based on the discrimination results for each block, has been used as a means of discriminating whether it is a character image or a gradation image. Value image and shading ii'jji
``Binarization processing method for manuscripts containing mixed images'' (IEICE Transactions VOI, .J87-B No. 7 (1984) p.
p781-788), and the so-called pixel-by-pixel processing method in which processing is performed on a pixel-by-pixel basis even if information on surrounding pixels is taken in, for example, the technique described in Japanese Patent Application Laid-Open No. 104372/1982 is known. .

(Problems to be Solved by the Invention) Among the above-mentioned discriminating means, a wide discriminator that discriminates each block is used, for example, by examining the dispersion of density within the block of interest, and if the dispersion is large, it is determined that it is a character stroke. There are ways to do this. According to this jll alternative method, if 111 is incorrectly classified, all of the blocks will be processed incorrectly, resulting in a severe deterioration in quality.

In addition, in general, discrimination for each block requires more memory to temporarily store image data than for each pixel, which is expensive, and the signal processing is also difficult. jt }
It has the disadvantage of becoming 1#.

On the other hand, the pixel-by-pixel discrimination method has advantages such as having fewer side effects of incorrect ↑ discrimination and requiring relatively little memory, but this method is difficult to distinguish between clearly printed characters and photographs. It was for the purpose of identification. Therefore, no process has yet been proposed for automatically discriminating even dark characters such as halftone drawings and general handwritten characters.

In addition, when using a printer that forms images using multi-valued signals, the multi-value processing required of the image processing unit differs between character images and gradation images. There was no image processing device.

The present invention has been made in view of the above-mentioned problems, and its purpose is to enable single-image processing of halftone line drawings without degrading the image quality, and to simplify the circuit configuration at that time. The present invention is intended to realize an image processing device capable of performing high-quality image processing suitable for each characteristic of a scale, a character image, and a gradation image.

(Means for Solving the Problems) The present invention solves the above-mentioned problems by applying a threshold value suitable for multi-value processing of character images and multi-value conversion of gradation images to image signals obtained by scanning a document. A mixed image consisting of a multi-value processing means for converting into a multi-value single word using a threshold suitable for processing, and a first discriminating means and a second discriminating means for discriminating the image into a gradation image and a character image. ↑Image of the separation method and this mixed discrimination method↑11
and an image selection means for selecting an output from the multi-value processing means based on a different result, and after the first discrimination means classifies the image signal into a plurality of types pixel by pixel, the second discrimination means selects the output from the multi-value processing means. The present invention is characterized in that it is configured to re-discriminate the separation result from the first discriminating means.

(Function) In the image processing device of the present invention, the image signal is
The pixel is classified into the type of antinode number by another means, and is further discriminated again by the second discrimination means. This t. Based on the II-based results, a result of multi-value processing performed using a threshold suitable for multi-value processing of character images or a threshold suitable for multi-value processing of gradation images is selected.

(Example) Hereinafter, an example of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a block diagram showing the electrical structure of an embodiment of the present invention.

First, the overall general operation of the embodiment shown in FIG. 1 will be explained.

An optical image obtained by optically scanning a subject (original) 1 is guided to an image reading section 3 via a lens system 2 and converted into an electrical signal (image signal). This image signal is converted by the A/D converter 4 into a digital image signal of predetermined bits. At the same time, the shading correction section 5 performs shading correction. Then, the effective area extraction section 6 selects only digital image signals corresponding to a necessary area (for example, B4 size, etc.). This digital image signal has an angle q
The image quality correction section 7 corrects the resolution by MTF correction jE. Thereafter, the digital image signal is supplied to the image processing section 8, and different image processing (multi-value processing of two or more values) is performed for the character image and the gradation image. This image processing 1 image discrimination will be described later. The multivalued digital image signal is supplied to a printer 10, such as an electrophotographic printer, where image processing is performed. Note that by operating the output selection section 9 provided in the operation section of the device, it is possible to select either a character image or a gradation image. You can also manually select one of the image processing options.

Next, the operation of the image processing section 8 will be mainly explained.

Now, in the present invention, the image processing section 8 performs multivalue processing according to the human image. In the present invention, 111 pixel-by-pixel processes are selected as the image-by-image processing to be performed during the multilevel quantization process.

The digital image signal after the MTF correction is first supplied to a character image processing section 20 which functions as a multi-value processing means, and undergoes image processing specific to character images so that characters and the like are clearly reproduced. A high-bass convolution filter is applied to output characters clearly.

Here, what is a high-pass convolution filter?
The pixel of interest is a. For example, the pixel of interest is multiplied by 6, then the pixels on the top, bottom, left, and right are subtracted, and the result is then multiplied by 1/1 for normalization. 2 and return to the original pixel.

Therefore, the filtered output of the pixel of interest a1 is aB-(1
/2)*Σ(C++*a++). Here,
C+1 is 6 for the pixel of interest, -1 for the 4 pixels on the top, bottom, left, and right.
, and the other diagonal precepts are 0. Of course, this result is O
It is post-processed to have a value between .

The digital image signal further passes through the low-pass filter 31 that constitutes the mixed image i11 separation means 50, and is supplied to the halftone processing section 21 functioning as a multi-value processing means, where it is given a predetermined gradation characteristic.

The reason why the digital image signal is first passed through the low-pass filter 31 and then supplied to the halftone processing section 2l is that by reducing the high frequency components of the image signal, moiré fringes and the like occur during halftone drawings. This is to make it more difficult.

The low-pass filter is not a dual-use configuration, but the halftone processing section 2
It may be provided independently for one use.

The digital image signal is further supplied to the mixed image discrimination means 50, and the image discrimination output (referred to as a second image discrimination output, in this example, 1-bit data) obtained thereby is sent to the image selector 22. Supplied as a control signal. The above-mentioned character images and gradation images are selected according to the image content by the second image discrimination output.

That is, when the image is determined to be a character image, the image discrimination output becomes "0" and the output of the character image processing section 20 is selected.
When it is determined that the image is a gradation image, the image discrimination output becomes "1" and the output of the halftone processing section 21 is selected.

Here, reference numeral 9 indicates an output selection section provided in the operation section of the digital copying apparatus.

■The power selection unit 9 has three types of selection switches: character mode, gradation mode, and mixed mode, and when character mode or gradation mode is selected, mixed image discrimination means 50
Regardless of the output result from the printer 10, only the fixed selected mode will be output to the printer 10.

On the other hand, when the mixed mode is selected, one of the gradation image processed data and character image processed data for each pixel is automatically output by the image ↑ separate output from the mixed image discrimination means 50 described above. selected and output. Therefore,
Even if text and gradation images are mixed on the same document,
By selecting the mixed mode, character image processing and gradation image processing are each selected, so image output quality is maintained.

FIG. 2 is a characteristic diagram showing the document density in the character image processing section 20 in such a case, its occurrence rate, and the threshold value when performing multi-value processing.

FIG. 3 is a characteristic diagram showing the document density in the halftone processing section 21 in such a case, its occurrence rate, and the threshold value when performing multi-value processing.

In other words, as shown in Figure 2, in the case of character images, the white level of the background should be at the lowest level (■ in Figure 2), and the black part of the characters should be at the highest density (Figure 2). ■),
A threshold value in the character image processing section 20 is set. At this time,
For example, in the case of processing into five values, four threshold values are arranged at irregular intervals. That is, so-called multi-value processing, which is the relationship between input image data and output printer data, is performed to emphasize white and black so as to be suitable for character images.

In addition, as shown in FIG. 3, in the case of a gradation image, the original density and its occurrence rate are approximately normally distributed, so the threshold values in the halftone processing section 21 are arranged approximately evenly ( Figure 3 ■～■).

Such multi-value processing using a threshold value is easily performed using a lookup table using a ROM. Fourth
The figure is a configuration diagram showing an example of the structure of this type of lookup table. The look-up table 23 shown in this figure shows a case where the multi-value processing sections of the character image processing section 20 and the halftone processing section 21 are configured with a ROM of one tit. In this le sokup table 23, the second 'I'll
The internal table is switched by the image discrimination signal from the separate means 40. That is, in this embodiment, the storage area of the ROM is divided into two blocks, and each block stores information for multi-value quantization.

Next, the mixed image I'll separation means 50 will be explained in detail. The mixed image discriminating means 50 described above is composed of first and second discriminating means 30 and 40.

That is, the first discrimination means 30 is a means for roughly discriminating a human image into a character image and a gradation image to obtain a first image discrimination output. On the other hand, the second II distinguishing means 40 to which the first stroke discrimination output is supplied specifically identifies the gradation picture image ▼ included in the first picture I'll distinguishing output corresponding to the character picture.
This is means for re-separating the 11 separate outputs and obtaining the second image 1'll separate outputs related to the character image and the gradation image.

Here, the first determining means 30 will be explained in detail.

The 1i11 separate means 30 includes a low-pass filter 31 for the pixel of interest, a comparator 32 that compares the low-pass output for the pixel of interest with a reference value REF, and a level determination circuit 33 that further determines the level of the comparison output for the pixel of interest. Ru.

The purpose of the low-pass filter 31 is to reduce the high frequency components of the human image signal, thereby making it possible to roughly distinguish between character images and gradation images.

When the high frequency component of the input image information is reduced, when the input image is a photographic image or a halftone line drawing, the density of the pixel of interest is dispersed to each point, so that every pixel exhibits a certain density Na or higher. .

To take a halftone image as an example, as shown in FIG. 5A, the difference in density between dots and non-dots clearly appears. When this is passed through a low-pass filter 31 to reduce high frequency components, a signal (approximate to a sine wave) corresponding to the repeating pitch of the halftone line image is generated at a DC level Na' above a certain level Na, as shown in Figure B. Obtained by superimposition.

On the other hand, even if characters, line drawings, etc. are passed through the low-pass filter 31, since there are many background parts, a region with a density lower than that of Na remains.

Therefore, the density of the pixel of interest is divided into 111 parts by the comparator 32 using a reference value REF having a predetermined level that is less than or equal to Na.

This standard value REF corresponds to a normal character stroke of 21ii! It is necessary to set the value to a value that is considerably lower than the threshold value when converting the image, and slightly higher than the background level. This is because if it is too low, it becomes indistinguishable from the background (ground) texture level, and if it is too high, when the halftone line drawing is filtered and dispersed, there will be some that are lower than this reference value REF, resulting in erroneous classification.

Therefore, it is preferable to set the reference value REF after detecting the background level in combination with a so-called automatic density adjustment function that determines the background level from the preliminary reading of the original.

In the case of photographs and halftone drawings, the comparison output is "1",
In the case of character drawings and line drawings, it is rOJ.

Next, in the level determination circuit 33, the comparison output obtained from the comparator 32 is re-determined.

In this re-judgment process, a check window of a certain size is set up around the pixel of interest, and only when all the pixels existing within that window are equal to or higher than the reference value REF mentioned above, does the pixel of interest change its gradation level. It is torn apart as a picture.

Through this processing, in the case of a halftone image, the density is widely dispersed, so that it is determined as a gradation image, so in this case, the halftone processing section 21 is selected based on the image discrimination output.

On the other hand, even if the character image is dispersed by background etc., a value lower than the reference value remains, and since a part of the check window is placed over this portion, the pixel of interest is separated from the character image as expected.

FIG. 6 shows an example of the low-pass filter 31, and in this example, a 3×3 convolution filter configured in a cross shape is used.

The convolution filter used as a low-pass filter is a process that returns the pixel of interest a0 and its surrounding pixels to the original pixel of interest by applying a certain weight C+1. In addition to that, it is divided by 5 and averaged.

Therefore, the pixel of interest a. The filtered output a′ is a′ ++− <1/5)*Σ(c ++* a +
+).

Here, C. is 1 only for the pixel of interest and the four pixels on the top, bottom, left, and right, and is 0 for the other diagonal components.

Here, the reason why a cross-shaped type with a weight of 1 is adopted as the low-pass filter 31 is as follows.

First, regarding the size of the filter, the larger the filter size, the more dispersed the results will be, making it possible to handle even coarse dots. However, since the overall density level at that time gradually decreases, it becomes difficult to determine the threshold value, and misjudgment becomes more likely to occur. Additionally, as the filter size increases, hardware constraints also increase.

For this reason, in this example, the size is set to 3×3 in consideration of hardware constraints.

The reason why the filter shape is made into a cross shape will be explained with reference to FIG.

In this figure, the center portion is a mesh dot, and the diagonal lines are a mesh pattern. Also, a collection of small dots is the minimum unit of reading.

Generally, in the case of halftone drawings, halftone lines are often arranged in a 45 degree direction. In the case of a cross shape, the result of filtering spreads nicely into a diamond shape along the mesh structure as shown in the figure. Therefore, no matter which pixel the window falls on, there is no extremely low part, and it is determined as a halftone image as expected.

On the other hand, if a filter that disperses in an X-shape is used, as shown in Figure 8, when the mesh lines are fine, in some areas even the dots of the adjacent mesh lines will be averaged out, and the density will be considerably reduced. It gets expensive. On the other hand, the filter action does not reach the valleys of the X-shape, so the density in these valleys remains low.

Therefore, if a part of the window falls over this valley, this part falls below the reference value, and the pixel of interest is incorrectly determined to be not a gradation image. This can occur regardless of the shape of the window.

From the above, it can be seen that a cross shape is appropriate as the shape of the filter.

Further, in order to distribute the dots evenly, it is desirable that the coefficients of each filter are all 1 (ie, equal).

It is expected that this low-pass filter 31 will effectively disperse even fairly coarse halftone lines.

Please note that the meshwork is too coarse or the dots are extremely small (
In other words, if the image is thin (thin), the filter will not be able to cover it, and there is a possibility that it will be misidentified as a text area.

Since the dots that can cause such misjudgment are always independent minute dots, if necessary, an independent dot detection circuit can be provided as post-processing after the low-pass filter 31, thereby further improving the halftone image detection ability.

In this post-processing, for example, check the pixels around a pixel that has been determined as black, and if all are white, it is considered an independent dot and 11
It is possible to employ means such as separating the images into different colors and performing halftone drawing processing.

The filter mentioned here has a 3 x 3 cross shape in order to maximize the effect with the minimum amount of hardware, but it must have enough resolving power to resolve the difference between the density after dispersion by the filter and the background density. For example, a filter with a larger structure can also be used.

In that case, halftone dots can be smoothed more efficiently than when the size is 3×3. In this case, in order to achieve more uniform smoothing, a cross-shaped filter is used that extends from the pixel of interest by n pixels (n is an integer of 1 or more) in the vertical and horizontal directions, and the total number of filters is 40 +
A filter having a structure that returns an average value of one pixel to the pixel of interest is preferable.

Here, a specific example of the low-pass filter 31 will be explained with reference to FIG.

The digital image signal is supplied to cascade-connected latch circuits 31a and 3lb for IH (l{represents a horizontal scanning period), and the original digital image signal and the digital image signal delayed by 1H and 2H are sent to amplifiers 31c and 31d. ,31
The signals are simultaneously supplied to the 3-line memory 31f via the line 31f.

Of the three lines of digital image signals obtained from the three line memory 31f, the n-1 line digital image (the image signal is generated by a pair of latch circuits 31 whose delay time is τ for one pixel)
g, 31h, and then supplied to the adder 31n.

Similarly, n-line digital image signals are sent to the adder 31 through three latch circuits 31i, 31j, and 31k, respectively.
n. The digital image signal obtained on the n+1 line is supplied to the adder 31n via a pair of latch circuits 31 (1.31m).

In this way, by using a plurality of latch circuits, all the digital image signals of each pixel shown in FIG. 8 can be obtained simultaneously. The fully added digital image signal is reduced to 1/5 by the coefficient unit 310 at the subsequent stage. Coefficient unit 3
As 1o, a ROM or the like can be used.

Next, the level determination circuit 33 will be explained. level 11
As the 1-constant circuit 33, a cross-shaped 7×7 check window is used as shown in FIG. This window extends 3 pixels vertically, horizontally, and vertically.
Pixel of interest a. If a total of 12 pixels including the above-mentioned pixel are larger (darker) than the above-mentioned reference value REF, the pixel of interest is determined to be a gradation image.

The reason why the window size is set to 7×7 will be explained with reference to FIG.

Generally, characters and line drawings often run parallel to the paper surface (that is, parallel to main scanning or sub-scanning). At this time, unless the outline of the scene is clearly processed as a character part, it will become blurred and difficult to see if it is subjected to gradation processing, for example.

As shown in the figure, if the area starts from the n-th pixel,
Due to the action of the low-pass filter 31, the density is dispersed up to n-1 pixels. If the window size is 7.times.7, and the arm of the window is up to n-2 pixels, there will be a portion lower than the reference value, and the pixel of interest will be determined to be a character image.

In other words, up to n+1 pixel rows are determined to be character parts. That is, in a boundary portion (outline portion), up to two pixels inside the boundary portion are reliably determined to be character portions.

Due to the effect of this window, a clear image can be obtained without blurring the outline at the border.

As is clear from the explanation of FIG. 11, the window size used in the level determination circuit 33 is preferably larger than the window size of the low-pass filter 31.

If the size of the low-pass filter 31 is assumed to extend by n pixels in the top, bottom, left and right directions, then the level determination window has a structure in which it extends by m pixels in the top, bottom, left and right directions, where m is an integer larger than n.

FIG. 12 shows a specific configuration example of the level publication circuit 33.

level t. Since the I1 constant circuit 33 also has a window configuration, it is basically the same as the filter configuration shown in FIG. However, the human input to the level judgment circuit 33 is the low-pass filter 31.
The determination output is a 1-bit signal indicating whether it is a character image or a gradation image.

However, since the window used in the level 111 constant circuit 33 has a size of 7×7, it is necessary to delay by 7 lines and 7 pixels. Therefore, for the IH delay used and 1
The only difference is that the number of latch circuits for pixel delay increases accordingly.

33a to 33[ are latch circuits for IH delay;
g is a memory for 7 lines. And 33h ~33
j. 33r to 33t are latch circuits for delaying four pixels.

Although these latch circuits each consist of four latch circuits connected in cascade, they are shown as one latch circuit for convenience in the drawings. 33k to 33q indicate latch circuits for one pixel.

These seven lines of digital image signals are each delayed by a predetermined pixel by a plurality of latch circuits, and
By deriving the output from each predetermined position, digital image signals of each pixel corresponding to the window shown in FIG. 10 can be obtained simultaneously in time.

Therefore, when the corresponding digital image signals are ANDed in the AND circuit 33u, an image discrimination output in which the pixel of interest becomes "1" is obtained at the output terminal only when the density level of all pixels is equal to or higher than the reference value.

In this way, in the first discriminating means 30, the character stroke group,
Separate outputs of the first image 1'11 corresponding to the photographic image and the halftone image group are obtained.

By the way, under certain conditions, a character image may be recognized as a character image or as a gradation image.

For example, as shown in FIG. 13A, when the input image is the character image "Sono", if this is passed through the low-pass filter 31, it will be output as shown in FIG. 13B. In other words, it can be seen that when a character becomes smaller than a certain level, the inside of the character becomes considerably blurred due to the action of the low-pass filter.

At this time, if there is a pixel of interest inside the character, and all of the pixels in its vicinity exceed the reference density due to this filter effect, the pixel of interest will be processed as a pixel of a gradation image. As a result, for example, even if an image is recognized as a character image as shown in Figure 14, there may be parts inside the character that are incorrectly identified as gradation images.
There are some parts that are +1 different.

In this way, the inside of a small character may be misidentified as a gradation image, and as a result, the quality of the character may deteriorate significantly.

Here, in a real halftone drawing or photographic drawing, the part that is judged to be a gradation drawing occupies a certain area, so it is actually not possible for such gradation drawings to be scattered in a certain area. There isn't. In other words, when a discrimination result in which gradation images are scattered for a very small area is obtained, there are actually no gradation images for each small area, so the discrimination result is It can be determined that the result is a mistake III.

Therefore, as shown in FIG. 1, a second determining means 40 is provided. This second discrimination means 40 re-discriminates the gradation picture included in the above-mentioned character picture as a character picture.

In order to re-recognize a gradation image included in a character image as a character image, it is only necessary to change the gradation image discrimination area and determine whether the gradation image occupies a certain size or not.

To do this, it is sufficient to memorize the image data of a certain area for the pixel of interest, and calculate the table or area of the closed area of the gradation image discrimination part.

In principle, it is necessary to store image data in both the main scanning direction and the sub-scanning direction to perform this discrimination process, but in the example described below, due to node constraints, image data is stored only in the main scanning direction. It has been realized.

As a result, it is sufficient that the memory has a maximum capacity of one bit indicating whether the image is a character image or a gradation image and one line of memory. Furthermore, experiments have revealed that the correction effect is sufficient even with only main scanning.

FIG. 15 shows a second discriminating means 40 that accomplishes such processing.
An example is shown below.

The first image discrimination output output from the first discrimination means 30 is supplied to the input terminal.

As mentioned above, the first image discrimination output is "1" when it is a gradation image.
The output is "0" when it is a character stroke.

The length of the gradation image of the first image discrimination output is counted by a counter 40a. Therefore, this counter 40a is set at "1" and reset at "O", and is counted up in synchronization with the dot clock CK. Counter output a is compared in comparator 40b with reference value b, which is associated with reference length L (FIG. 16A). For L, it is best to have about 2 questions.

The pulse comparison output exceeding the reference value b becomes "1", and at this time, the pulse generating means 40d outputs a small control pulse p (FIG. 16B).

On the other hand, the dot clock CK is also supplied to the address counter 40e to form a horizontal address, and the address data is latched in the latch circuit 40f.

The latch pulse is 11 on the first picture! It is formed based on the rising edge of the discriminatory output.

40g indicates this rising edge detection circuit.

One of the address data of the address counter 40e and the rising address data latched by the latch circuit 40f is selected by the address selector 40h by the control pulse p. In this example, it is assumed that the latched address data is selected when the control pulse p is obtained. Address data selected by address selector 40h is supplied to first line memory 40i.

A control pulse p is supplied to the first line memory 40i as a write enable pulse. Therefore, when the control pulse p is obtained, the first image 1? Data "1" at a predetermined level is written at the latched address in synchronization with the rising point 0 of the Il separate output.

On the other hand, in the second line memory 40j, the first image discrimination output is written to the address obtained from the address counter 40e in synchronization with the dot clock CK (FIG. 16C)
).

Data is read from the line memories 40i and 40j as shown in FIG. That is, in the next first line, data is simultaneously read from the line memories 40i and 40j (FIGS. 17A to 17C).

The output of the line memory 40i passes through a NAND circuit 40k
It is supplied to the set terminal S of the S-type flip-flop 40n. Similarly, each output of the line memories 40i and 40j is supplied to a NAND circuit 4011 that does not require human input, and the output is further passed through a NAND circuit 40m to a flip-flop 4.
0n reset terminal R.

As a result, outputs for the second two images I'll as shown in FIG. 17D are obtained at the output terminal 40o.

When the second 111 separate means 40 is configured in this way, as shown in FIG. Only when the value is equal to or greater than L, an image discrimination output "1" indicating a gradation image can be set as the final image discrimination output.

Therefore, if the length is less than the predetermined length L, even if it is determined to be a gradation image, it will ultimately be re-identified as a character image (FIG. 17).

As a result, manual manuscripts can be identified and processed with precision and efficiency not previously possible. Furthermore, halftone drawings, which have been considered difficult in the past, can now be determined as gradation drawings by using the low-pass filter 31 and window processing for level determination.

Further, since halftone processing is performed based on the output of the low-pass filter 31, a good image with less moiré can be obtained. Even character information with low contrast, such as handwritten characters, can be clearly determined to be text because it is compared with the background texture information, and there is no misidentification within the characters, so human images can be correctly identified and processed.

In addition, in the above example, only the length of the gradation image part was evaluated and the judgment was made, but similarly, a correction circuit that incorrectly judges an extremely short character part as I'll is added, and the judgment result is may be modified to bring it closer to reality.

Based on the final I'll results obtained in this way, in the case of character strokes, the character stroke processing unit 20 is selected, and in the case of gradation images, the low-pass filter 31 is used in advance, or halftone The processing unit 21 selects the result passed through a unique low-pass filter. An image output is obtained by sending the result to a printer.

Next, an example of a mechanical section of a digital copying apparatus to which the image processing apparatus of this embodiment is applied will be explained with reference to FIG.

When you turn on the copy button on the device, the document reading section A
is driven. First, the original 1 on the original table 111 is optically scanned by the optical system.

The optical system includes a carriage 114 provided with a light source 115 and a reflecting mirror 116, which moves integrally with the carriage 114, and converts the light from the document 1 by the light source 115 to one mirror 119 of a V-mirror, which will be described later. Mirror 1
17 and V-mirrors 119 and 119' that are moved in the same direction at half the speed of the mirror 117. The carriage 114 and the V-mirror 119, 119' are moved by a sliding rail (
(not shown). As the light source 115, a halogen lamp or a commercially available warm white fluorescent lamp can be used.

A standard white plate 110 is provided on the upper surface side of the left end of the document table 111 . This is done by scanning the standard white plate 110,
This is to normalize the image signal to the reference white signal.

An optical image obtained by irradiating the original 1 with the light source 115 is guided to the optical information conversion unit 100 via the anti-1.1 mirror 117 and the -mirror 119, 119'. This optical information conversion unit}100 consists of a lens 100a and a CCD 101 that functions as an image reading means.

The image signal photoelectrically converted by the CCD 101 is outputted to the writing section B after being subjected to the various signal processing described above in the signal processing system.

The writing section B has a deflector 150. As the deflector 150, in addition to a galvanometer mirror or a rotating polygon mirror, a deflector made of an optical deflector using a crystal plate or the like may be used. The laser beam modulated by the image signal passes through this deflector 15.
Deflection scanning is performed by 0.

The modulated beam scans (main scans) over a photosensitive drum (image-shaped body) 110 that is uniformly charged by a charger 121 . Through this main scanning and the sub-scanning caused by the rotation of the drum 110, an electrostatic latent image corresponding to the image signal is formed on the drum 110.

The electrostatic latent image is developed by a developing device 123 containing black toner.

On the other hand, the recording paper fed from the paper feeder 141 via the feed roll 142 and the timing roll 143 is conveyed to the lower surface side of the drum 110 in a state in which the timing is synchronized with the rotation of the drum 110. Black toner is transferred onto the recording paper by transfer +5:130 to which a high voltage is applied, and then separated by a separation pole 131.

The separated recording paper is conveyed to a fixing device 132, subjected to a fixing process, and then discharged.

Drum after transfer 1. 1 0 is cleaning device 1
It is cleaned at 26 and prepared for the next imaging process. Here, 127 is a cleaning blade, 128 12
9 is a metal roll to which a predetermined DC voltage is applied.

In the above description, the image processing apparatus of this embodiment is applied to a digital copying machine, but the present invention is not limited to this. That is, it goes without saying that the present invention can be applied to various devices that process character images and gradation images.

(Effects of the Invention) As described above in detail, in the present invention, a mixed image in which a character image (including a character image with a tone) and a gradation image coexist is used as the first and second image fl! The discrimination is made based on the 111 results, and multi-value processing is performed using different thresholds for character images and gradation images. In other words, if it is judged to be a gradation image, the result of multi-value conversion processing that emphasizes white and black is selected and output, and if it is judged to be a gradation image, the result of multi-value conversion processing that also emphasizes the intermediate gradation is selected and output. I decided to do so. Therefore, it is possible to realize an image processing apparatus that can perform high-quality image processing suitable for each image.

[Brief explanation of the drawing]

FIG. 1 is a configuration diagram showing the electrical configuration of an embodiment of the present invention;
Figure 2 is a characteristic diagram showing the state of multi-value conversion processing in the character image processing section, Figure 3 is a characteristic diagram showing the state of multi-value conversion processing in the halftone processing section, and Figure 4 is a characteristic diagram showing the state of multi-value conversion processing in the halftone processing section. 5 is an explanatory diagram for explaining the operation of the low-pass filter. FIG. 6 is a diagram showing the structure of the low-pass filter. Fig. 8 is an explanatory diagram explaining the characteristics of the low-pass filter, Fig. 9 is a schematic diagram showing the electrical configuration of the low-pass filter, and Fig. 10 is a diagram showing the structure of the level judgment circuit. 12 is an explanatory diagram for explaining the characteristics of the level determination circuit, FIG. 12 is a diagram showing the electrical structure of the level determination circuit, FIG. 13 is an explanatory diagram of the filter effect, and FIG. 14 is an illustration of the image t. FIG. 15 is a configuration diagram showing the structure of the 21'll different means, FIG. 16 and FIG. 17 are explanatory diagrams of the operation of the second discriminating means, and FIG. FIG. 1 is a configuration diagram showing the mechanical configuration of a copying machine to which an image processing apparatus according to an embodiment is applied. 1... Subject 2... Lens 3... Image @
Reading section 4... A/D converter 5... Shading correction section 6... Effective area extraction section 7... Resolution correction section 8...
・Image processing section 9...Output selection section 10...Printer 20...Character image processing section 21...Halftone processing section 22...Image selector 30...First sorting means 3-・Low-pass filter 32...Comparator
33...Level t. I1 constant circuit 40...2nd ↑ separation means 50...Mixed image i'11 separation means 2nd section Fig. 3 Fig. 23 Fig. 5 Fig. 6 section 3x3 convolution filter d: ΣC;7. a;'' Wa t: part

Claims (1)

[Claims] Image signals obtained by scanning a document are converted into multi-value signals using a threshold value suitable for multi-value processing of character images and a threshold value suitable for multi-value processing of gradation images. a multi-value processing means for discriminating an image into a gradation image and a character image; a mixed image discriminating means comprising a first discriminating means and a second discriminating means for discriminating the image into a gradation image and a character image; and an image selection means for selecting an output from the multi-value processing means, and after the first discrimination means classifies the image signal into a plurality of types pixel by pixel, the second discrimination means selects the output from the first discrimination means. An image processing device characterized in that the image processing device is configured to re-discriminate the determination result from the .