JPH0478268A - Picture binarizing processor - Google Patents

Abstract

PURPOSE:To reduce the capacity of a storage device by measuring number of black picture elements for each binary dot information calculated by a same weight coefficient and using individual information as address information of the storage device. CONSTITUTION:A picture signal obtained by scanning lines of an intermediate tone picture is converted into a digital data and fetched by a comparator 12 together with a binarizing threshold level data from a ROM 13 and compared. As a result, the signal is outputted as the binarizing digital data corresponding to the picture signal and delayed at a shift register 14 and fed sequentially to shift registers 15-18. A parallel data extracted by the registers 14,16,18 corresponds to the position of the weight coefficient and bits of a same weight coefficient are collected and inputted respectively to measuring devices 19-22, in which number of black picture elements is counted and its information is inputted to a ROM 13 as an address data. Thus, the capacity of the ROM or the like is reduced.

Description

[Detailed Description of the Invention] [Object of the Invention] (Industrial Application Field) The present invention is an image binarization method useful when reproducing images having halftone levels using a binary recording device such as a dot printer. Regarding equipment.

(Prior Art) Recently, images having halftone levels, such as photographic images, have been displayed and output using simple binary recording devices such as dot printers. Since this type of recording apparatus can only display binary images of black and white, it is necessary to effectively convert the halftone image into a binary image. Regarding this binarization process, for example, in photographs published in newspapers, etc., a screen is used to create a shading effect by utilizing the mesh size, but this method is applied to the Mama Dot printer, etc. That is extremely difficult.

Therefore, in the past, attempts have been made to binarize halftone images by typically introducing binarization processing such as the texture dither method or the minimum average error method.

The tissue dither method is achieved by a simple process in which an appropriate threshold value is determined in advance according to the pixel position, and pixel signals are discriminated and binarized using this, but compared to the above-mentioned minimum average error method, it is generally The drawback is that the image quality is poor.

On the other hand, the minimum average error method determines binarization so that the average difference between the binarized image and the original image within a small area made up of multiple pixels is small, and the image quality is sufficiently improved. However, it has drawbacks such as the binarization process being complicated and requiring a large-scale system configuration.

Therefore, considering these circumstances, Tokikai 57-10436
9, the average density approximation method, which can obtain a binary image with the same quality as that obtained by the minimum average error method and can be realized at low cost with a simple hardware configuration, is a binary method for halftone images. We provide conversion equipment. This method performs binarization based on the area ratio occupied by black dots in a small region, that is, the average density. This average density is the dot that will be binarized from now on and the area around it that has already been binarized.
It is calculated for the dots that have been converted into values, and from now on 2
The black and white dots to be converted into values are determined by calculating the average density when the dot is black and the average density when it is white, checking which one is closer to the input signal, and selecting the one that is closer.

The basic configuration of this system consists of a line buffer for storing binary dot information that has already been binarized, a storage device such as a ROM, and a comparator.

However, the capacity of a storage device such as a ROM that calculates the average density requires at least the address bits for the binary dot information that has already been binarized, and it is also necessary to expand the binary dot information to be referenced. Under the present circumstances, it is necessary to increase the number of storage devices such as ROM.

(Problems to be Solved by the Invention) As described above, in the above-mentioned apparatus, when creating a binarization threshold value from the average density using a storage device such as a ROM, only the binary dot information that has already been binarized is used. address pits are required at the minimum, making it impossible to reduce the capacity of storage devices such as ROM.

Therefore, it is an object of the present invention to provide an image binarization processing device that can eliminate this problem and reduce the capacity of the storage device such as the ROM.

[Structure of the invention]

(Means for Solving the Problem) In order to achieve the above object, the present invention provides an input means for inputting an image signal obtained by raster scanning an image, and an input means for inputting an image signal obtained by raster scanning an image, and an input means for inputting an image signal obtained by raster scanning an image, and an input means for inputting an image signal obtained by raster scanning an image. A predetermined weighting process is performed based on past binarized data,
creating means for creating binarized threshold data for the current input image signal; and forming means for forming binarized data for the current input image signal by comparing the binarized threshold data and the current input image signal. , a means for outputting this binarized data, temporarily storing it, and feeding it back as past binarized data in the binarization process.
In the value conversion processing device, the creation means includes a measuring means for respectively measuring the number of black pixels calculated using the same weighting coefficient in the weighting process, and a measuring means for calculating the number of black pixels calculated by the same weighting coefficient in the weighting process, and using the measured value of the measuring means as address information for the current input image signal. It is characterized by comprising a storage means for storing binarized threshold value data.

The present invention also provides an input means for inputting an image signal obtained by raster scanning an image, and an input means for inputting an image signal obtained by raster scanning an image, and based on past binarized data obtained by binarizing the current input image signal and the previously input image signal. A predetermined weighting process is performed to create binarized threshold data for the current input image signal, and by comparing this binarized threshold data and the current input image signal, the binarized data for the current input image signal is generated. In the image binarization processing apparatus, the image binarization processing apparatus includes a forming means for forming the binarized data, and a means for outputting the binarized data, temporarily storing it, and feeding it back as past binarized data in the binarization process, the forming means , a measuring means for respectively counting the number of black pixels calculated by the same weighting coefficient of the weighting process, and a binary value for the current input image signal using the J1 measurement value of the measuring means and the current input image signal as address information. The invention is characterized by comprising a storage means for storing converted data.

(Function) In the present invention, in order to calculate the average density, the binary dot information that has already been binarized is calculated by calculating the number of black pixels for each binary dot information calculated using the same weighting coefficient. Measure the
The number information is used as the address information of the storage device. This allows the capacity of the storage device to be reduced.

(Embodiments) Hereinafter, embodiments of the present invention will be described with reference to the drawings.

Figure 3 shows the relationship between halftone image 1 and pixel 2, which is separated by sampling after raster scanning the halftone image.
b) shows a part of it enlarged. Now, let the input image be r(j, j), and 2 at this image position (i, j)
When value data is defined as g(i, j), it can be expressed as O≦f(j, j)≦] g(i, j)=Oor 1 . In other words, the input image f(j, j) at the image position (j, j) has a normalized level of 0 to 1, and the binarized data g(i,
This indicates that j) takes 0 or 1. Now, the third
In FIG. 2B, it is assumed that the pixel 2a indicated by diagonal lines is the data position to be processed, and that the pixel 2b has already completed the binarization process and the binarized data has been determined. Note that 2c indicates an unprocessed pixel. In this way, the pixel 2a shown in FIG. 3(b).

2b and 2c are the extracted areas around the pixel 2a to be processed, Q is the set of pixels 2b for which processing has been completed, and Q is the set consisting of this set Q and the pixel 2a to be processed.
-, the algorithm for binarization processing using this method is shown as follows.

g(M,N)=FIf'(M,N)1g(i,j)[(
i, j)E Q]l However, the coordinates (M, N) indicate the pixel position to be processed, and F is a function. In other words, the binarized data g (M, N) of the pixel position (M, N) to be processed is combined with the human image signal data r (M, N) of the same pixel position and the neighboring pixels included in the set Q. Pixel position (i
, j) and the already binarized data g(i, j), it is determined by some weighting function F. The interval number F is, for example, shown here as follows. However, α(i, D are weighting functions having weights as shown in FIG. 2, for example).

As shown in this algorithm, by predetermining a weighting function, the binarized data for the above image signal data is created simply from the past binarized data and the input image signal data at the current coordinate position. , this can be output. Moreover, since all the past data required for this binarization process is binary data, it is easy to accumulate and store it.

Furthermore, according to this configuration, the value X described above can be found, and the binarized data g (river, N) can be found by comparing the value X with the coefficient α(0,0). In other words, by determining the following, the binarized data g(M, N) can be directly obtained. Here, the right side of the above equation is past data g(i
, j).

In order to realize the above method, conventionally the calculation on the right side of the above equation is R
Register it in OM in advance and use it as past binarized data
g(i) because it was accessed at (+, j).

Address bits equal to the number of address bits j) were required.

By the way, the term in the above equation was being determined. Therefore, if we pay attention to the above equation, it can be expressed as, where the weighting coefficient α(M-i, N-j) as shown in FIG. For example, the same weighting coefficient α(M−i
, Nj), the terms are put together and g(i, j)
The total sum may be obtained by multiplying the number of black pixels by the weighting coefficient α(M-i, N-j).

FIG. 1 is a schematic diagram of an embodiment of an apparatus according to the present invention that implements the above algorithm. An image signal input manually by line-scanning a halftone image is converted into n-bit digital data via, for example, an A/D converter 11, and then captured. This n-bit image signal data is taken into a comparator 12 together with n-bit binarized threshold data from a ROM (read only memory) 13, which will be described later, and compared, and based on the result, it is determined whether the image signal corresponds to the above-mentioned image signal. It is output as binary digital data. Needless to say, A/D converter 11
An image correction circuit such as a shading correction circuit or an automatic gain correction circuit may be provided between the comparator 12 and the comparator 12 as necessary.

10-bit binary digital data, which will be described later, is input to the ROM 1B as address data, and n-bit binary threshold data created based on the algorithm described above is output.

The binary 1-bit data outputted from the comparator 12 in this way is supplied to a predetermined output device (not shown) and is delayed by two samples via the shift register 14, and then sequentially transferred to the shift registers 15, 16. Provided on .17.18. The shift registers 15 and 16 are configured in series to delay the above bit data by one line scanning period, and from each tap of the shift register 16 in the subsequent stage, bit 2 of adjacent, for example, 5 samples (5 pixels) position is delayed. Valued data is extracted in parallel. Shift registers 17 and 18 are similarly arranged in series to delay 1-bit data by 1 line scanning period, and 1-bit binary data at 5 sample positions are taken out in parallel from the subsequent stage.

A total of 12 bits of parallel data taken out in parallel from these shift registers 14, 16, and 18 are as follows:
For example, it corresponds to the position of the weighting coefficient as shown in FIG. 4, and conventionally, this 12-bit data was input as is as address data of the ROM 25 as shown in FIG. The other configurations in the conventional example shown in FIG. 5 are the same as those shown in FIG. 1.

Therefore, in this embodiment, the bits of the same weighting coefficient are input to the measuring devices 19, 20, 21, and 22 respectively, and the information obtained by counting the number of each black pixel is stored in the ROM 1B.
input as address data.

That is, now is the timing t. The output from the A/D converter is n-bit image signal data (Co.

CI, C2-C, , ), the same timing t. 2, one sample before the shift register 14.
Valued data Dl,, 2 samples ago binary data D12
is being output. Furthermore, the parallel output of the shift register 16 is binary data D (L-21+D+L-1)I D-L, where the number of line scanning samples is L.
・D-(,,+I)+D-(L・2) ・The parallel output of the shift register 18 is the binary data D
-+2L-21+ D-+2L Ll + D-2
L + D-(2L+Il +D-(21, +21).

Therefore, when applying a weighting coefficient matrix as shown in FIG. 4, for example, the measuring device 19 receives 2-bit binary data D-, 2t2) r D
+2L, 2. The 2-bit count result of the black pixel at that time is output and inputted to the ROM 13, and the measuring device 20 receives 4-bit binary data D-L corresponding to the weighting coefficient 3.
2+, -11・D12L+11D (L-21+
D-fL+21 is manually operated, outputs the 3-bit count result of the black pixel at that time, inputs it to ROM1.3,
1 contains the 4-hit binary data D corresponding to the weighting coefficient 5.
−21,・D −(,,+++ D−口−・1)D
-2 is input, the 3-bit count result of the black pixel at that time is output and input to the ROM 1.3, and the measuring device 22 receives 2-bit binary data D Ll corresponding to the weighting coefficient 7.
D is input, and the black pixel count result 2 at that time is
The bit is output and manually input to the ROM13.

Here, the data Co-C, corresponds to f(M, N) in the algorithm described above, and the data D-,
,D-2,D ,L-2,~D-(L bow 1.D-,
The 12-bit data 2L-21 to D-f2L+2+ correspond to g(i, j) [i, je Q], respectively.

Furthermore, the n-bit binarization threshold data registered in advance in ROM 1.3 is calculated and created based on the above algorithm, and in the above embodiment, a shift register is used for the line delay of the binary data. Did you use this in RAM?
(random access memory) and may be controlled by an address controller.

FIG. 2 shows another embodiment of the invention. In this embodiment, the ROMI 3 and comparator 12 shown in FIG.
It is constructed by replacing the part with the ROM 23. In this example, the measuring instruments 19.20.21.22
The ROM 23 is addressed by a total of (10+n) bits of data, including the measurement data output from the A/D converter and the n-bit data output from the A/D converter, and a desired binary image signal is output. The other configurations are similar to those shown in FIG.

Note that the present invention is not limited only to the above embodiments. For example, the pixel area Q and number of pixels of past binarized data to be fed back to the binarization process, and the weighting function α may be determined according to specifications. In particular, the present invention
This is very effective because when the pixel area Q is expanded, the area of a storage device such as a ROM is not expanded.

〔Effect of the invention〕

As explained above, in order to calculate the average density, this device does not manually input binary dot information that has already been binarized to the address of a storage device such as a ROM, but instead uses the same weighting coefficient. Since the number of black pixels of the binary dot information calculated by is measured and the number information is input to a storage device such as a ROM, the capacity of the storage device such as a ROM can be reduced. This is because when creating a gate array, measuring instruments are incorporated inside the gate array, but storage devices such as ROM cannot be inserted, so it is difficult to reduce the capacity of storage devices such as ROM that are external to the gate array. is important.

[Brief explanation of drawings]

Fig. 1 is a block diagram showing one embodiment of the present invention, Fig. 2 is a block diagram showing another embodiment of the invention, Fig. 3 is a diagram explaining the concept of pixel position and image processing, Fig. 4 5 is a diagram illustrating an example of a weighting function, and FIG. 5 is a block diagram illustrating a conventional example of the present invention. 11... A/D converter, 12... Comparator, 13.2
3, 5... ROM, ] 4°] 16° shift register, 1. 2... Measuring instrument.

Claims (2)

[Claims] (1) An input means for inputting an image signal obtained by raster scanning an image; creating means for performing weighting processing to create binarized threshold data for the current input image signal; and generating binarized data for the current input image signal by comparing the binarized threshold data and the current input image signal. a forming means for outputting the binarized data and temporarily storing the binarized data;
In the image binarization processing apparatus, the image binarization processing apparatus includes means for feeding back past binarized data in the digitization process, wherein the creation means measures the number of black pixels calculated using the same weighting coefficient in the weighting process. 2 for the current input image signal using the measured value of the measuring means as address information.
1. An image binarization processing device, comprising: storage means for storing digitization threshold data. (2) input means for inputting an image signal obtained by raster scanning an image; Performing weighting processing to create binarized threshold data for the current input image signal, and compare this binarized threshold data with the current input image signal to form binarized data for the current input image signal. a forming means, for outputting the binarized data and for temporarily storing it;
In the image binarization processing apparatus, the image binarization processing device includes means for feeding back past binarized data in the digitization process, wherein the forming means measures the number of black pixels calculated using the same weighting coefficient in the weighting process. An image binarization processing apparatus, comprising: means for storing binarized data for the current input image signal using the measured value of the measuring means and the current input image signal as address information.