JPH1093815A - Image forming device and image processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processor which can precisely decide even a document image where a character area, a dot photograph area and a photograph coexist. SOLUTION: A period structure calculation part 3 calculates the period structure of the image from an image signal 1 inputted from an image area means. A decision part 5 decides the type of the image with the period structure calculated in the period structure calculation part 3. A filtering part 6 executes a filtering processing based on the judged result of the judgment part 4 for the inputted image signal 1. A binarization (multivalued) part 8 binarizes (multivalued process) the output of the filtering part 6 and outputs a binarization (multivalued) signal 9. The outputted binarization (multivalued) signal 9 is sent to an image output means.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention identifies a character image or a photographic area in an image to be processed for a document image used in a general office input by an office automation device such as a scanner, a facsimile, a copying machine, and the like. Also, the present invention relates to an image processing apparatus that performs high-quality image reproduction and reduces transmission cost / time by performing different image processing for each region, and an image forming apparatus using the same.

[0002]

2. Description of the Related Art In general, in a document image processing apparatus which can handle not only code information but also image information, a document read by an image reading means such as a scanner can be used with image information having contrast such as characters and diagrams. Performs simple binarization using a fixed threshold value, and image information having a gradation such as a photograph is binarized by a pseudo gradation converting means such as an error diffusion method. This is because, when the read image information is subjected to simple binarization processing using a fixed threshold value, the resolution of the character and line image areas is preserved, so that the image quality does not deteriorate. Is not stored, the image is degraded.

On the other hand, if pseudo gradation processing such as an error diffusion method is performed on the read image information, the image quality is not deteriorated because the gradation of the photographic image area is preserved. Since the resolution of the image is reduced, the image is deteriorated in image quality. That is, if a single binarization process is simply performed on the read image information, it is impossible to simultaneously satisfy the image quality of each region having different characteristics.

Therefore, in order to binarize a document image in which characters and photographs are mixed to simultaneously satisfy the resolution of the characters and the gradation of the photograph, it is necessary to perform an area such as a character, a photograph, a halftone dot, etc. from the document image. Is subjected to image region separation and binarization suitable for each region is performed, or a spatial filter process suitable for each region (for example, a character region is a high-frequency emphasis filter,
It is necessary to perform no binarization by using a specific pseudo-gradation means by performing a filter without a filter in a photographic region and a low-pass filter in a halftone dot region.

Similarly, when transmitting a read original such as a facsimile apparatus, it is desirable to select, for each area, a compression method having a good compression rate for characters and line drawings and a method having a good compression rate for photographs.

To solve the above problem, as a method of separating a character and a photograph region, for example, Japanese Patent Laid-Open No. 58-3374 proposes a method of identifying an image region for each block. This method is a method in which a target image is divided into blocks, and areas are separated based on density changes in the blocks. At that time, density changes such as a small change in density in a photo, a large change in density in a text and halftone picture, a large cycle of density change in a character, and a small cycle of density change in a halftone picture Utilizing the nature of

The details will be described below. First, the target image is divided into (m × n) pixel blocks. next,
The maximum density signal and the minimum density signal in the block are obtained, and the maximum density difference signal in the block, which is the difference between them, is calculated. Next, a preset threshold value and a maximum density difference signal are compared, and if the maximum density difference signal is equal to or smaller than the threshold value, a photographic area is used. If the maximum density difference signal is larger than the threshold value, a non-photograph area is used. By doing so, the photographic area and the non-photographic area (character and halftone photographic area) are separated. next,
Further, when the image in the block is at a density level at which all images are all white or all black, it is determined to be a character area. With the above procedure, the character and photograph areas can be separated, and appropriate binarization processing can be performed on each area.

[0008]

In general, the image area separation method including the image area separation method described above has the following problems. That is, the printed halftone photographic image is 65 to 20.
There are many different numbers of lines spanning zero lines. The prior art is effective for a halftone dot photograph having a high screen ruling, but it is difficult to separate a halftone dot photograph having a low screen ruling because the character and the feature are similar. Further, it is impossible to distinguish between halftone printing and line printing such as copy output.

Therefore, the present invention can accurately determine even a document image in which a character area, a halftone dot photograph area, and a photograph area coexist, and can use a more appropriate binarization / gradation processing method. Provided are an image forming apparatus and an image processing apparatus that can binarize a character area with good resolution and a binary area with good gradation for a photographic area and a halftone photographic area. The purpose is to:

[0010]

According to the present invention, there is provided an image forming apparatus, comprising: an image reading means for reading a target image and outputting the image signal; and a frequency of the image based on the image signal output from the image reading means. Periodic structure calculating means for calculating a structure; determining means for determining the type of the image based on the periodic structure calculated by the periodic structure calculating means; and determining means for an image signal output from the image reading means. And image forming means for forming an image corresponding to the image based on image processing data processed by the image processing means. doing.

The image forming apparatus of the present invention further comprises a color image reading means for reading a color target image and outputting the color image signal, and the image forming apparatus based on the color image signal output from the color image reading means. A periodic structure calculating means for calculating the frequency structure of: a determining means for determining the type of the image based on the periodic structure calculated by the periodic structure calculating means; and a color image signal output from the color image reading means. Color conversion means for converting the color image signal into a second color image signal based on the determination result of the determination means for the second color image signal output from the color conversion means. Image processing means for performing image processing, and image forming means for forming a color image corresponding to the color target image based on the image processing data processed by the image processing means It is equipped with.

Further, the image processing apparatus of the present invention comprises a periodic structure calculating means for calculating a periodic structure of the image from an image signal inputted by reading the image to be processed, and data obtained by the periodic structure calculating means. Determining means for determining the type of the image from the image data.

The image processing apparatus according to the present invention further comprises a periodic structure calculating means for calculating a periodic structure of the image by performing a Fourier transform in a certain direction from an input image signal after reading the image to be processed; Determining means for determining the type of the image from the data obtained by the periodic structure calculating means.

Further, the image processing apparatus of the present invention performs a main scan and a sub-scan on an image to be processed, thereby reading an image from the image and inputting a one-dimensional Fourier transform in a main scan direction of the image. Periodic structure calculating means for calculating a periodic structure of the image by performing conversion and one-dimensional Fourier transform in the sub-scanning direction; and determining means for determining the type of the image from two data obtained by the periodic structure calculating means Is provided.

Further, the image processing apparatus according to the present invention includes a periodic structure calculating means for calculating a periodic structure of the image by performing a two-dimensional Fourier transform from an image signal input by reading an image to be processed; Determining means for determining the type of the image from the data obtained by the structure calculating means.

The image processing apparatus of the present invention scans an image to be processed at a plurality of angles from an input image signal and performs one-dimensional Fourier transform in each scanning direction. The image processing apparatus further includes a periodic structure calculating unit that calculates a periodic structure of the image, and a determining unit that determines a type of the image from a plurality of data obtained by the periodic structure calculating unit.

Further, the image processing apparatus according to the present invention comprises a periodic structure calculating means for calculating a periodic structure of the image from an image signal inputted by reading an image to be processed, and data obtained by the periodic structure calculating means. And an image processing means for performing different image processing for each of the judgment areas on the input image signal based on the judgment result of the judgment means.

According to the present invention, a printed matter or a copy output having a characteristic image structure can be identified by performing frequency analysis on a window including an image signal of a pixel of interest in an image to be processed and calculating a periodic structure of the image. Thus, it is also possible to distinguish between a photograph and a character portion.

Therefore, for example, regions such as characters, photographs, and halftone dots are separated from a document image, and binarization suitable for each region is performed, or a spatial filter process suitable for each region (for example, , A high-frequency emphasizing filter for a character area, no filter for a photographic area, and a low-pass filter for a halftone area, and binarization can be performed by a specific pseudo-gradation means, and high-quality image reproduction can be performed. . Similarly, when transmitting a read original such as a facsimile apparatus, it is possible to select, for each area, a compression method having a good compression rate for characters and line drawings and a method having a good compression rate for photographs.

[0020]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 schematically shows a configuration of the image processing apparatus according to the present embodiment. FIG.
In FIG. 1, reference numeral 1 denotes an image signal, which is inputted by an image reading means such as an image scanner (not shown). Reference numeral 2 denotes an image type determination unit, which includes a periodic structure calculation unit 3 and a determination unit 4. Reference numeral 5 denotes a determination signal output from the determination unit 4, reference numeral 6 denotes a filtering unit, reference numeral 7 denotes a filtering signal output from the filtering unit 6, reference numeral 8 denotes a binary (multi-value) conversion unit, and reference numeral 9 denotes a binary (multi-value) conversion unit. Binary (multi-value) output of 8
And sent to an image output means (not shown).

In such a configuration, a document image to be processed is read by image reading means such as an image scanner, and an image signal 1 is input, for example, as digital data of 8 bits per pixel. The input image signal 1 is sent to the periodic structure calculator 3.
The periodic structure calculator 3 calculates a periodic structure of the image from the input image signal 1. The data of the periodic structure calculated by the periodic structure calculation unit 3 is sent to the determination unit 4. The determination unit 4 determines the image type based on the data from the periodic structure calculation unit 3 and outputs a determination signal 5 as a result of the determination.

The decision signal 5 output from the decision unit 4 is sent to a filtering unit 6. The filtering unit 6
A filtering process is performed on the input image signal 1 based on the determination signal 5, and a filtering signal 7 as a result is output. This output filtering signal 7
Is sent to the binarization (multi-value) conversion unit 8. The binarization (multi-level) conversion unit 8 performs binarization (multi-level) processing on the filtered filtering signal 7 and outputs a binarization (multi-level) signal 9.
The output binary (multi-level) signal 9 is sent to image output means (not shown).

Hereinafter, the image type determining section 2 will be described in detail. FIG. 2 schematically illustrates the configuration of the image type determination unit 2. In FIG. 2, reference numeral 11 denotes C which controls the overall control.
PU (Central Processing Unit), 12
Is a program memory for storing programs to be executed by the CPU 11, work data, and the like.
A page memory for storing one page of an image signal 1 of 8 bits per pixel, a determination memory for storing a result of determining an image type by a periodic structure, a reference numeral 15, a CPU 11, a program memory 12, a page memory 13, a determination memory 14 is a bus connecting them.

Next, details of calculation and determination processing of the periodic structure by the image type determination unit 2 in such a configuration will be described with reference to a flowchart shown in FIG. First,
In step S1, a window for calculating a frequency structure is set. This window is, for example, an (n × m) window as shown in FIG.

Next, in step S2, FIG.
× n) one-dimensional FFT (Fourier Function Transform)
fer: Fast Fourier Transform) shown in FIG. 4 while moving the (1 × m) area shown in FIG.
Xm) to calculate the frequency component by repeatedly performing the operation within the window.

Next, in step S3, the frequency components repeatedly calculated in step S2 are averaged. FIG.
It is an example of the frequency spectrum obtained in step S3. Next, in step S4, a frequency fmax having the maximum intensity is calculated from the frequency components obtained in step S3. Next, in step S5, the maximum intensity frequency fma
Based on x, for example, identification determination is performed according to the following determination criteria.

Fmax ≦ fth: printing halftone dot, line printing (copy output) fmax <fth: character In this determination, generally, the printing halftone dot is formed of a series of minute dots, and the frequency of the image is It focuses on the fact that it is higher than a character image. Similarly, the image frequency is high for line printing such as copy output. This determination result is stored in the determination memory 14 in step S6.

Various methods are conceivable for determining the image type using the frequency component. In the above example, an example is shown in which the print halftone and the character are discriminated and determined. However, the continuous photograph and the print halftone can also be identified. This is to make the determination based on the frequency distribution range of the image as shown in FIG. In other words, the printing halftone dot has an image structure with a fixed period, so that the distributed frequency range is narrow, while the continuous photograph is relatively wide. When the intensity for each frequency f is P (f), a preset threshold value Pth is compared with P (f),
By obtaining the number of P (f) larger than Pth, the distribution frequency range is obtained. That is, W: the number of P (f)> Pth is defined. If W is greater than the threshold Wth, a continuous photograph,
If smaller, it is determined to be a printing dot.

W ≧ Wth: continuous photograph W <Wth: print dot Further, when the target image is a color image, it is possible to identify the print dot of the continuous photograph by using the number of peaks in the frequency spectrum (see FIG. 9). In color printing, Y (yellow), M (magenta), C (cyan), K (black)
The dots of each plate (color) are arranged at a constant frequency at different screen angles. That is, when the periodic structure is viewed in the one-dimensional direction, each plate (color) has a slightly different frequency, and three or four peaks appear on the frequency spectrum. Therefore, by calculating the number of peaks, it is possible to discriminate between a continuous photograph and a printed halftone dot. That is, when the number of peaks is Pn, Pn = 1: continuous photograph Pn ≧ 3: color printing halftone.

By using the above method, it is possible to determine a color print and a monochrome print. That is, Pn = 1: monochrome printing halftone Pn ≧ 3: color printing halftone.

When it is desired to distinguish between print halftone dots or continuous lines and continuous line prints such as copy output, the following method is effective. In the image structure of the line screen seen in the copy output, the frequency structure appears in only one of the main scanning and the sub-scanning. On the other hand, when the screen angle is 45 °, the printing halftone has the same frequency spectrum in the main scanning and the sub-scanning, and the frequency spectrum is different at other screen angles, but both periodic structures appear.

In the case of a continuous photograph, when the main scanning and the sub-scan are compared, almost the same frequency spectrum is obtained. Therefore, the number of peaks in the frequency spectrum in the main scanning direction is compared with the number of peaks in the frequency spectrum in the sub-scanning direction, and if the numbers are different, it can be determined that the output is a copy output. That is, the number of peaks in the main scanning direction is P
m, and the number of peaks in the sub-scanning direction is Ps: (Pm = 1 and Ps = 0) or (Pm = 0 and Ps =
1): Copy output Other than the above: Judgment as print halftone is possible.

Using the same principle, when the peak frequency in the main scanning direction is fm and the peak frequency in the sub-scanning direction is fs, it can be determined that fm = fs: printing halftone fm ≠ fs: copy output. it can.

The above examples all show the case where a one-dimensional frequency structure is calculated by a one-dimensional FFT and discrimination is made.
These are extended to two dimensions, the frequency structure is calculated using two-dimensional FFT, and the type of the image is identified and determined using the presence or absence of the spectrum peak, the frequency distribution range of the peak, and the frequency distribution range of the entire image. Is possible. The identification method is the same as the one-dimensional case, but by making it two-dimensional,
The discrimination accuracy is further improved.

In the above example, the one-dimensional frequency structure of the main scanning or the sub-scanning is calculated. However, the image type can be identified by scanning the image at a plurality of angles and calculating the respective frequency structures. It is. For example, a color print dot has four screen angles, so scanning an image at various angles will result in significant peaks at four angles on the frequency spectrum. The identification determination can be performed using the number of angles at which a remarkable peak appears.

Further, in the above example, the case where the window as shown in FIG. 4 is set and the window is moved for each pixel to perform the discrimination determination on a pixel basis has been described. Can also be set to

Hereinafter, an example of an algorithm used in the above-described FFT processing will be briefly described using a time domain division method which is a typical FFT operation algorithm.
Now, when the number of data (n shown in FIG. 5) is a power of 2,
That is, assuming that n = ^2x , the calculation procedure has a flow as shown in the flowchart of FIG.

First, in step S11, the complex array X (i) (i = 0, 1,..., N-1) is initialized. That is, n pieces of sampling data are substituted into the complex array X (i) for the real part and all imaginary parts are set to “0”. Next, in step S12, the bits are rearranged in the reverse order, and a reverse order counter is obtained. Table 1 below shows an example of performing the bit reverse order.

[0039]

[Table 1]

This processing procedure is generally described in FIG.
As in step S21 of the flowchart shown in FIG. 1, the values of the reverse rotation counter are sequentially stored in the array t (i). In step S22, the value of the complex array X is copied to another array R, and in step S23, , I = 0 to n−
The values of the complex array X are sequentially rearranged in the order of bits in the reverse order based on the following equation.

X (i) = R (t (i)) Next, for X (p) (p = 0, 1,..., N−1),
The first stage butterfly operation is performed (S13). this is,
Starting from p = 0, this is an operation in which the arrays are taken one pair at a time, and their sum is returned to the beginning and the difference is returned to the later.
When this operation is performed n / 2 times, the first stage ends.

The butterfly operation of the second stage is performed every other one (S14). This starts at i = 0 and moves to i = 1 when two pairs are calculated at i = 0. Again, if we calculate two pairs, i
Is incremented by one. The twiddle factor Wn ^K required for this butterfly operation (= EXP (-j2πK / n), where K is an integer)
Are WN ⁰ , WN ^{N / 4} ), and the second stage is i = n / 4-1.
The operation ends.

The butterfly operation at the third stage is based on X (p) and X
(P + 4) pairs. The twiddle factor is WN ^{hN / 8} (h =
0, 1, 2, 3). The value of i is increased for each calculation of four sheets, and the calculation ends with i = n / 8-1.

The butterfly operation of the (s + 1) -th stage is represented by X (p)
And X (p + 2 ^s ) (S15). The twiddle factors are WN ^kP (k = 0, 1,..., 2 ^s-1 ) and P = 2 ^ms-1 . Starting from 0, i is incremented by 1 every time the butterfly operation of 2 ^s is performed with p = i · 2 ^{s + 1} + h, and the calculation at this stage ends when i = 2 ^{ms− 1} −
This is the time when 2 ^s butterfly operations at the time of 1 have been completed.

The final stage is the m-th stage, and X (h) ± WN ^h
A butterfly operation of X (h + n / 2) (h = 0, 1,..., N / 2-1) is performed N / 2 times (S16). With the above procedure, the one-dimensional FFT operation can be performed.

The calculation and determination processing of the periodic structure are performed in the above-described procedure. The filtering unit 6 adaptively performs a filtering processing according to the type of the image based on the determination result, and outputs a filtering signal 7. For example, the area determined to be a character area is the area shown in FIG.
FIG. 12B shows an example in which the high-frequency emphasis filter processing shown in FIG.
A low-pass filter process as shown in FIG. The calculation method of the filter shown in FIG. 12A is as follows.

F (i, j) = 4 ^* f (i, j) -f (i, j-1) -f
(i, j + 1) -f (i-1, j) -f (i + 1, j) where f (i, j) represents a pixel of interest, and i and j are pixels in the main scanning direction, respectively. Represents the pixel position in the sub-scanning direction.

The filtering process can be easily realized by a combination of a multiplier and an adder. Next, the binarization (multi-level) conversion section 8 binarizes the filtering signal 7 output from the filtering section 6 (multi-level). Less than,
The binarization (multi-value) unit 8 will be described. Here, an example of binarization will be described. In this example, the density of the target pixel is already 2
This is a method of adding a value obtained by multiplying a binarization error of a valued peripheral pixel by a certain weighting factor and binarizing it with a fixed threshold.

FIG. 13 shows a schematic configuration of the binarizing section 8 for performing a binarizing process by the error diffusion method. In FIG. 13, 21 is an input image signal, 22 is a correction circuit for correcting image information of a target pixel, 23 is a corrected image signal, 24
Is a binarization circuit for binarizing the corrected image information of the target pixel, 25 is a binarized image signal, and 26 is a binarization error calculator for calculating a binarization error of the binarized target pixel. , 27 is 2
A binarization error signal; 28, a weight coefficient storage unit for storing a weight coefficient for calculating a weight error; 29, a binarization error calculated by the binarization error calculation unit 26; A weight error calculating unit for calculating a weight error by multiplying, 30
Is a weight error signal, 31 is an error storage unit that stores the weight error calculated by the weight error calculation unit 29, and 32 is an image correction signal.

Hereinafter, the binarization processing of the binarization section 8 will be described in detail. The input image signal 21 is subjected to a correction process in a correction circuit 22 by an image correction signal 32 described later, and a corrected image signal 23 is output. Corrected image signal 2
3 is compared with a binarization threshold Th (for example, 80h, h indicates a hexadecimal number) in the binarization circuit 24, and if the corrected image signal 23 is larger than the binarization threshold Th, “1” (black pixel) is output as the binarized image signal 25, and “0” (white pixel) is output if the value is small.

In the binarization error calculator 26, the corrected image signal 23 and the binarized image signal 25 (here, 0h when the binarized image signal 25 is "0", ff when "1")
h) is calculated, and the difference is calculated.
Output as In the weight error calculating section 29, the weighting coefficients A, B, C,
D (however, A = 7/16, B = 1/16, C = 6/1
6, D = 3/16) is calculated.

Here, * in the weighting coefficient storage unit 28 indicates the position of the pixel of interest, and the binarization error of the pixel of interest is multiplied by the weighting coefficients A, B, C, and D, and the peripheral pixels of the pixel of interest (weighting coefficient A weight error of pixels corresponding to the positions of A, B, C, and D) is calculated.

The error storage unit 31 stores the weight error signal 30 calculated by the weight error calculation unit 29. The weight error of four pixels calculated by the weight error calculation unit 29 is stored in the pixel of interest *. On the other hand, eA, eB, eC, e
The result is added to the area D and stored. The aforementioned image correction signal 3
Reference numeral 2 denotes a signal at the position of *, which is a signal obtained by accumulating weight errors of a total of four pixels calculated by the above procedure.

According to the image processing apparatus configured as described above, it is possible to accurately determine even a document image in which a character area, a halftone photographic area, and a photographic area are mixed. Furthermore, if an appropriate binarization / gradation processing method is used, the character area can be binarized with good resolution, and the photographic area and the halftone photographic area can be binarized with good gradation. can do.

Next, a case where the present invention is applied to an image forming apparatus for forming a duplicate image of a color image will be described.
FIG. 14 shows a schematic configuration of an image forming apparatus such as a digital copying machine for forming a duplicate image of a color image. Note that the same parts as those in FIG.

In FIG. 14, a color image reading section 41 as a color image reading means is constituted by, for example, an image scanner composed of a CCD type color line sensor or the like. Red), G (green), and B (blue) light are converted into electrical signals corresponding to the three primary colors, and each pixel is an 8-bit digital signal, that is, each of R, G, and B is eight.
It is output as a bit image signal 1.

The image signal 1 output in this way is sent to the periodic structure calculating section 3. The periodic structure calculator 3 calculates a periodic structure of the image from the input image signal 1.
The data of the periodic structure calculated by the periodic structure calculation unit 3 is sent to the determination unit 4. The determination unit 4 includes the periodic structure calculation unit 3
, The image type is determined based on the data from, and a determination signal 5 is output as the result. When a color photograph is distinguished from a color halftone dot, the determination can be made using the number of peaks in the frequency spectrum as shown in FIG.

On the other hand, the color conversion section 10 outputs an R, G, B 8-bit image signal (color data) input for each pixel.
1 represents three primary colors of ink for forming a color image: C (cyan), M (magenta), Y (yellow), and K (black).
Is converted into an 8-bit second image signal (color data) corresponding to the amount of the color material, and is sent to the filtering unit 6.

The color converter 10 will be described with reference to FIG. Generally, the data of the three primary colors R, G, and B of the light obtained from the color image reading unit 41, that is, the first color data R, G, and B are converted into the three primary colors of the ink that controls the amount of the color material for forming the color image. Data y (yellow), m (magenta), c
A masking equation is used as a method of color correction processing for converting to (cyan). The basic formula is represented by the following equation (1).

[0060]

(Equation 1)

Here, y, m, and c are the electric signal amounts (referred to as color signals y, m, and c) of the respective color materials y, m, and c obtained as a result of the masking, and R, G, and B are the colors. The R, G, and B electric signal amounts, Aij, are coefficients indicating the masking amounts. Basically, a masking circuit is configured based on Equation 1. One example is shown in FIG. The first color data R, G, and B are respectively
1a, 51b, 51c, and the coefficients A11, A12, A
Multiplied by 13.

Next, the multiplication results of the multipliers 51a and 51b are respectively input to the adder 52a, and the two are added. Then, the adder 52b adds the multiplication result of the multiplier 51c and the addition result of the adder 52a, and outputs the addition result as a color signal c.

Similarly, the first color data R, G, B input to the multipliers 51d, 51e, 51f and the coefficients A21, A2
2 and A23 are respectively multiplied by multipliers 51d and 51e.
Are multiplied by the adder 52c, the multiplication result of the multiplier 51f is added by the adder 52d, and the color signal m is output from the adder 52d.

Further, the first color data R, G, B input to the multipliers 51g, 51h, 51i and the coefficients A31, A3
2 and A33 are respectively multiplied, and multipliers 51g and 51h
Are multiplied by the adder 52e, and the multiplication result of the multiplier 51i is added by the adder 52f, and the color signal y is output from the adder 52f.

On the other hand, at the time of forming a color image, the under color removal UCR (Under
Color Removal) is used. The principle will be briefly described. When the same amount of each color material y, m, c is mixed, black color, that is, black is obtained.
The minimum amount of each of m and c is obtained, and this is set as the consumption amount of the color material black. That is, when the second color data K corresponding to the black consumption is defined, it can be expressed by the following equation.

K = MIN (y, m, c) MIN: function operation for obtaining the minimum value As a result, the second value corresponding to the consumption of each color material of y, m, c
Can be expressed by the following equation by removing a certain amount of black component obtained by the above equation from each consumption amount.

Y = y−K M = m−K C = c−K That is, by using the black (K) component, the amount of overlapping color materials is reduced, and the effect of reducing the consumption of each color material is obtained. Can be expected.

FIG. 16 shows a specific example of a UCR circuit which removes a certain amount of black components from the color signals y, m, and c and performs a UCR process to reduce the amount of each signal. In FIG. 16, the color signal c and the color signal m are compared in magnitude by a comparator 53a. The resulting signal (for example, 0 if the color signal c is small) is output to the selector 54a.

The color signals c and m are input to the input ports P0 and P1 of the selector 54a, respectively.
An input port (for example, input port P0 if color signal c is small) is selected by a control signal from 3a (for example, 0 if color signal c is small), and the signal is output. This output signal OUTP becomes OUTP = MIN (c, m).

Similarly, the signal OUT is supplied to the comparator 53b.
By inputting P and the color signal y, inputting the resulting control signal to the selector 54b, and inputting the signal OUTP and the color signal y to the input ports P2 and P3 of the selector 54b, the output signal OUTK becomes , OUTK = MIN (y, m, c), and the second color data K which is a digital signal of the black component amount is obtained.

Further, the color signal y and the second color signal K are input to a subtractor 55a, and the second color data Y is obtained by subtracting the signal K from the signal y. Similarly, the subtractor 5
5b, the second color data K is subtracted from the color signal m to obtain second color data M. The subtractor 55c subtracts the second color data K from the color signal c to obtain second color data C. Obtained respectively.

C, M,
The 8-bit image signal of each of Y and K is sent to the filtering unit 6, where the filtering process based on the determination result of the determination unit 4 is performed as described above, and the filtering signal 7 of C, M, Y, and K is output. Is done. Filtering signal 7
Is subjected to gradation processing by a binary (multi-value) conversion section 8 and binary (multi-valued) C, M, Y, K color data is output.

C, output from the binarization (multi-value) conversion section 8,
The M, Y, and K color data is sent to a color image forming unit 42 as an image forming unit. Color image forming unit 42
Are, for example, C, M,
An image corresponding to the image read by the color image reading unit 41 is formed (hard copy) by attaching an amount of color material corresponding to the Y and K color data to the recording paper.

As the color image forming section 42, for example, a so-called laser printer which forms an image by using exposure scanning with a laser beam and an electrophotographic process is used.

[0075]

As described above in detail, according to the present invention, the periodic structure of an image is calculated by performing frequency analysis on a window including an image signal of a pixel of interest in an image to be processed.
It is possible to identify a printed matter or a copy output having a characteristic image structure, and it is also possible to distinguish a printed matter or a character part from a photograph or a character part.

Therefore, for example, regions such as characters, photographs, halftone dots, etc. are separated from the document image and binarization suitable for each region is performed, or a spatial filter process suitable for each region (for example, , A high-frequency emphasizing filter for a character area, no filter for a photographic area, and a low-pass filter for a halftone area, and binarization can be performed by a specific pseudo-gradation means, and high-quality image reproduction can be performed. . Similarly, when transmitting a read original such as a facsimile apparatus, it is possible to select, for each area, a compression method having a good compression rate for characters and line drawings and a method having a good compression rate for photographs.

[Brief description of the drawings]

FIG. 1 is a block diagram schematically showing a configuration of an image processing apparatus according to an embodiment of the present invention.

FIG. 2 is a block diagram schematically illustrating a configuration of an image type determination unit.

FIG. 3 is a flowchart illustrating a frequency structure calculation and determination process performed by an image type determination unit.

FIG. 4 is an explanatory diagram of a window area used for calculating a frequency structure.

FIG. 5 is an explanatory diagram of a window area used for calculating a frequency structure.

FIG. 6 is an explanatory diagram of a window area used for calculating a frequency structure.

FIG. 7 is an explanatory diagram of a frequency spectrum.

FIG. 8 is a diagram for explaining image type determination.

FIG. 9 is a view for explaining image type determination.

FIG. 10 is a flowchart illustrating a processing procedure of a one-dimensional FFT algorithm.

FIG. 11 is a flowchart for explaining a bit inverse processing procedure of the one-dimensional FFT algorithm.

FIG. 12 is a diagram illustrating a filtering process.

FIG. 13 is a block diagram showing a schematic configuration of a binary (multi-level) conversion unit.

FIG. 14 is a block diagram schematically showing a configuration of an image forming apparatus according to an embodiment of the present invention.

FIG. 15 is a block diagram schematically showing a preceding stage configuration of a color conversion unit.

FIG. 16 is a block diagram schematically showing a subsequent configuration of a color conversion unit.

[Explanation of symbols]

1 ... image signal, 2 ... image type determination unit, 3 ... periodic structure calculation unit (periodic structure calculation unit), 4 ... determination unit (judgment unit), 6 ... filtering unit (filtering unit), 8 ... ... Binary (multi-level) conversion unit (gradation processing means), 10
... Color conversion section (color conversion section), 41... Color image reading section (color image reading section), 42... Color image formation section (color image formation section).

Claims (21)

[Claims] An image reading means for reading a target image and outputting the image signal; a periodic structure calculating means for calculating a frequency structure of the image based on the image signal output from the image reading means; A determining unit that determines the type of the image based on the periodic structure calculated by the structure calculating unit; and an image signal output from the image reading unit, which differs for each determination region based on the determination result of the determining unit. An image forming apparatus comprising: image processing means for performing image processing; and image forming means for forming an image corresponding to the image based on image processing data processed by the image processing means. 2. The image processing means according to claim 1, wherein said image processing means performs different filtering for each determination area based on a determination result of said determination means with respect to an image signal output from said image reading means, and filtering performed by said filtering means. 2. The image forming apparatus according to claim 1, further comprising a gradation processing unit that performs gradation processing based on the result. 3. A color image reading means for reading a color target image and outputting the color image signal, and a periodic structure for calculating a frequency structure of the image based on the color image signal output from the color image reading means. Calculating means; determining means for determining the type of the image based on the periodic structure calculated by the periodic structure calculating means; and a second color image signal based on a color image signal output from the color image reading means. A color conversion unit for converting the image data into a second color image signal output from the color conversion unit; and an image processing unit for performing different image processing for each determination area based on the determination result of the determination unit. Image forming means for forming a color image corresponding to the color target image based on the image processing data processed by the processing means, Image forming apparatus. 4. The filtering means for filtering the second color image signal output from the color conversion means for each determination area based on the determination result of the determination means. 4. The image forming apparatus according to claim 3, further comprising a gradation processing unit that performs gradation processing based on a filtering result of the filtering unit. 5. A periodic structure calculating means for calculating a periodic structure of the image from an image signal input by reading an image to be processed, and judging the type of the image from data obtained by the periodic structure calculating means. An image processing apparatus comprising: a determination unit. 6. The image processing apparatus according to claim 5, wherein said periodic structure calculating means calculates a periodic structure of the image by performing a Fourier transform from the input image signal. 7. A periodic structure calculating means for calculating a periodic structure of the image by performing a Fourier transform in a certain direction from an image signal input by reading an image to be processed, and a periodic structure calculating means. An image processing apparatus comprising: a determination unit configured to determine a type of the image from data. 8. The image processing apparatus according to claim 7, wherein the determination unit determines the type of the image based on a frequency range of the Fourier transform data obtained by the periodic structure calculation unit. 9. The image according to claim 7, wherein the determination unit determines the type of the image based on a wide distribution range of the entire Fourier transform data obtained by the periodic structure calculation unit. Processing equipment. 10. The image processing apparatus according to claim 7, wherein the determination unit determines the type of the image based on the number of peaks of the Fourier transform data obtained by the periodic structure calculation unit. 11. Performing a main scan and a sub-scan on an image to be processed, thereby obtaining a one-dimensional Fourier transform in the main scan direction and a one-dimensional Periodic structure calculating means for calculating a periodic structure of the image by performing Fourier transform; and determining means for determining the type of the image from two data obtained by the periodic structure calculating means. Image processing apparatus. 12. The image processing apparatus according to claim 1, wherein the determining unit determines a type of the image based on a difference between Fourier transform data in a main scanning direction and Fourier transform data in a sub-scanning direction from the two data obtained by the periodic structure calculating unit. The image processing apparatus according to claim 11, wherein the determination is performed. 13. The image processing apparatus according to claim 1, wherein the determining unit determines, based on the presence or absence of the peaks of the Fourier transform data in the main scanning direction and the Fourier transform data in the sub-scanning direction, from the two data obtained by the periodic structure calculating unit. The image processing apparatus according to claim 11, wherein the type is determined. 14. A periodic structure calculating means for calculating a periodic structure of the image by performing a two-dimensional Fourier transform from an image signal input by reading an image to be processed, and data obtained by the periodic structure calculating means. An image processing apparatus comprising: a determination unit configured to determine a type of the image from the following. 15. The image processing apparatus according to claim 14, wherein the determination unit determines the type of the image based on a frequency range of a peak of Fourier transform data obtained by the periodic structure calculation unit. apparatus. 16. The image processing apparatus according to claim 14, wherein the determination unit determines the type of the image based on a partial range of the entire Fourier transform data obtained by the periodic structure calculation unit. 17. The image processing apparatus according to claim 14, wherein the determination unit determines the type of the image based on the number of peaks of the Fourier transform data obtained by the periodic structure calculation unit. 18. A periodic structure of the image is calculated by scanning the image at a plurality of angles and performing a one-dimensional Fourier transform in each scanning direction from an image signal input by reading an image to be processed. An image processing apparatus comprising: periodic structure calculating means; and determining means for determining a type of the image from a plurality of data obtained by the periodic structure calculating means. 19. The image processing apparatus according to claim 18, wherein the determining unit determines the type of the image based on the number of data having a remarkable peak from the plurality of data obtained by the periodic structure calculating unit. Image processing device. 20. A periodic structure calculating means for calculating a periodic structure of the image from an image signal input by reading an image to be processed, and judging the type of the image from data obtained by the periodic structure calculating means. An image processing apparatus, comprising: a determination unit; and an image processing unit that performs different image processing on each of the determination regions based on a determination result of the input image signal based on a determination result of the determination unit. 21. A filtering unit that performs different filtering on each of the determination areas based on the determination result of the determination unit with respect to the input image signal, and based on a filtering result of the filtering unit. 21. The image processing apparatus according to claim 20, further comprising a gradation processing means for performing gradation processing.