JPS63204879A - Image processing method - Google Patents

Abstract

PURPOSE:To prevent an edge from emphasizing and a black part in a character from voiding by providing binarizing circuits in two stages. CONSTITUTION:In a first binarizing circuit 5, the binarization of an attended picture element is executed with a corrected signal 100 and an error signal 500 outputted from a second binarizing circuit 6; in case the attended picture element is decided to be white, a signal 200 representing black color and an error correcting signal 300 are outputted in order to assume the surrounding picture elements to be black. Also, in case the attended picture element is decided to be black, a signal 200 representing white and an error correcting signal 300 are outputted in order to assume the environmental picture elements to be white. In the second binarizing circuit 6, the binarization of the attended picture element is executed again by using error correction signals 300 and 400, and an error signal 500 and a binary signal 600 are outputted. the binary signal 600 is transmitted to a printer 7, where signals are converted into the presence/absence of dot and printed. As a result, an edge-emphasis and voiding within a character can be prevented.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of the Invention] The present invention relates to an image processing method in a digital printer, a digital facsimile, and the like.

[Prior art]

Conventionally, in order to reproduce halftones in digital printers, digital facsimiles, etc., methods of reproducing gradations using dithering methods or density pattern methods have been unsuccessful. However, with this method, edges may become cut off due to dithering in line drawings or text parts of the original, or
There were disadvantages such as the image quality deteriorated when the inside of the characters were blank.

[Purpose of the invention]

It is an object of the present invention to provide an image processing method that eliminates the drawbacks of the above-mentioned prior art and reproduces images of any original with high quality and high definition.

〔Example〕

Embodiments of the present invention will be described in detail below with reference to the drawings.

FIG. 1 is a block diagram showing one embodiment of the present invention. The input sensor unit 1 is composed of a photoelectric conversion element such as a CCD and a driving device that scans the element, and performs an operation of reading a document. The image data of the document read by the input sensor section 1 is sequentially sent to the A/D converter 2. Here, the data of each pixel is converted into 8-bit digital data, and the data is divided into two data having 256 levels of gradation. Next, correction circuit 3
Shape ink correction and the like are performed by digital calculation processing to correct uneven sensitivity of the CCD sensor and uneven illuminance due to the irradiation light source. Next, the corrected signals 101 and 100 are input to the error correction circuit 4 and the first binarization circuit 5, respectively.

In the error correction circuit 4, error calculation is performed using the signal 200 output from the first binarization circuit 5, and the error correction circuit No. 4
00 is output. In the first binarization circuit 5, the pixel of interest is binarized using the corrected signal 100 and the error signal 500 output from the second binarization circuit 6, and the pixel of interest is determined to be white. In this case, the surrounding pixels are assumed to be black, so
A signal 200 indicating black and an error correction signal 300 are output.

If the first binarization circuit determines that the pixel of interest is black, it outputs a signal 200 indicating white and an error correction signal 300 in order to assume that surrounding pixels are white. The second binarization circuit 6 again uses the error correction signals 300 and 400 to
Value conversion is performed, and an error signal 500 and a binary signal 600 are output. The binary code 600 is sent to the printer, where it is converted into dot on/off and printed.

FIG. 2 is a block diagram showing details of the first binarization circuit 5. As shown in FIG. Error signal 500 output from the second binarization circuit
is stored in the error buffer memory 24. The error buffer memory 24 stores errors for each processed pixel as shown in FIG. 6. If the error buffer memory corresponding to the pixel of interest currently being processed is represented by (i, j), The value of the error buffer memory of (i-1, j-1) is input. Similarly, LUT22b has (
f, j-f), but LUT22c has (i+1.j-1)
However, the value of the error buffer memory of (i-1,j) is input to the LUT 22d. L U T 22 a
In the NLU T 22 d, each input value is weighted and output to the adder 21 . In this embodiment, the weighting constants in LIT22 a NLUT 22 d are configured as -2-1-1-, respectively, but the weighting constants can also take other values. This is not the limit. Also, when the specified error buffer memory does not exist, that is, when the values of i-1 and j-1 are less than O, or when i+1 is larger than the total number of pixels in the main scanning direction,
Processing is performed with the value of the error buffer memory set to O.

The adder 21 sums the density data 100 of the pixel of interest to be processed and the data output from the LUTs 22a to 22d, outputs the sum, and outputs the sum as an error correction signal 300 to the second binarization circuit 16. Man-powered. On the other hand, this output signal is binarized by the comparator 23 with a threshold value of 127, and when the output signal is less than 127, the pixel is normally output as white to the printer section, but in this embodiment, the binarization circuit is converted into two stages. The first binarization circuit 5 outputs information opposite to the determined information of the pixel of interest as a signal 200.
Output as . This is because the output of the first binary circuit 5 is input to the error correction circuit 4 and used for weighting the pixels around the pixel of interest. , since the surrounding pixels are assumed to be black, the result (black) is inverted from the information (white) of the pixel of interest.

Similarly, when the output signal from adder 21 is greater than 127, signal 200 is output as white.

Although 127 is used here as the threshold value, it may be set to another value depending on the input level.

Furthermore, in this embodiment, four LITs are used to take into account errors in four surrounding pixels, but by increasing the number of LUTs, errors in more pixels can also be taken into account.

FIG. 4 is a block diagram showing details of the error correction circuit 4.

The corrected signal 101 output from the correction circuit 3 is taken into the line buffer 40. The line buffer 4'0 can store three lines of image data, and the image data is sequentially sent to latches 41a to 41g. 41a-41i
The latches are 31a to 31 as shown in FIG.
It corresponds to pixel i (31e is the pixel of interest), and 31a
It holds the pixel values of ~31i. Latch 41f~4
The values of 1t are input to subtracters 42a to 42d, respectively,
The difference with the signal 200 output from the first binarization circuit 5 is calculated.

The calculations performed here are as follows.

(Value of 41f) - (Signal 200) (Value of 41g) - (Signal 200) (Value of 41h) - (Signal 200) (Value of 411) - (Signal 200) Values calculated by subtractors 42a to 42d is input to the adder 43, where the sum is taken. Although this sum is weighted and used as the error correction signal 400, other suitable values may be used.

FIG. 5 is a block diagram showing details of the second binarization circuit 6.

The adder 51 adds the error correction signals 300.400 from the first binarization circuit 5 and the error correction circuit 4, and outputs the final error-corrected signal 700. This signal 70
0 is input to the subtracter through latch 53 and directly to comparator 52. The comparator 52 compares the signal 700 with the threshold value 127, and if the signal 700 is less than or equal to the threshold value 127, the signal is converted to 01, and if it is greater than the threshold value 127, it is converted to a binary code 60 of 255.
A zero is output, one to the subtractor 54 and the other to the printer. In the subtracter 54, (signal 700) - (
A subtraction (signal 600) is performed, and the result is output as an error signal 500. The error signal is stored in the error buffer memory 24 shown in FIG. 2 mentioned above. In the comparator 52, the threshold value is set to 127, but it may be set to another value depending on the level of the input signal.

The processing operations in this embodiment have been explained above, and will be explained below using more specific numerical values.

The corrected signal lO output from the correction circuit 3 in FIG.
Consider the case where O is at a level of 190 and signal 101 is the data shown in FIG.

Here, the data shown in FIG. 7 is 41f to 41i in FIG.
This is what is latched to.

Further, the error signal 500 (total sum of LUTs 22a to 22d in FIG. 2) from the second ternarization circuit 6 is assumed to be 30.

In this case, first, in the first binarization circuit, the data 190 of the corrected signal 100 and the L U T 22 are
A total of 30 from a to 22 d is added, resulting in 220 (1
90+30) is manually input to the comparator 23.

The comparator 23 performs temporary binarization, and when binarized using a threshold value 127, 220 becomes black. However, the signal 200 becomes O because the pixels around the pixel of interest are assumed to be white. Also, the signal 300 in FIG. 2 is 220.

Next, in the error correction circuit 4, in FIG.
The data latched in i (Figure 7) and the signal 200
(0) performs the calculation shown below and outputs a signal 400.

Here, the weighting coefficient was set to 1/64 as described above.

Next, the second binarization circuit 6 receives the signal 30 as shown in FIG.
0 (220) and the signal 400 (10) are added in the adder 51 (220+10=230), and the result is binarized in the comparator 52 (threshold value 1.27), and the L signal 600 is output as black. Then, it is printed by the printer 7.

By having a two-stage binarization circuit in this way, it is possible to weight the pixel of interest and its surrounding pixels so that they are blacker in areas where they are larger than the threshold (127), so processing is performed simply using the error diffusion method. In this case, the threshold value 1
Even data larger than 27 will be white, and the inside of the character will not appear white or disappear.

Further, as described above, in a portion where the surrounding pixels are smaller than the threshold value (127), the weight is increased so that the portion becomes whiter, so it is possible to prevent the occurrence of black dots in the white portion.

FIG. 8 is a diagram showing a case where the error correction circuit shown in FIG. 4 is partially modified.

Weighting circuits 44a to 44d are provided for the outputs of the subtracters 42a to 42d, respectively;
The sum of the outputs of d is taken by an adder 43, and an error correction signal 40 is obtained.
Outputs 0. The weighting constant used in the circuits 44a to 44d was 1155 for 44a and 44c, and 1/75 for 44b and 44d. In FIG. 3, the pixel distance between the pixel of interest 31e and the surrounding pixels 31f is determined by 31e
Since the distance between pixels 31g and 31g is different, the influence of the surrounding pixels on the pixel of interest 31e naturally changes. Therefore, as shown in FIG. 4, rather than weighting the output of the adder 43, it is better to weight the outputs of the subtracters 42a to 42d as shown in FIG. This is because it can be done well.

It is also possible to extend this embodiment and apply it to color images. One way to do this is to have a circuit for the three colors R (red), G (green), and B (blue) as shown in Figure 1 to process the three colors at the same time, or to process R first and then G. , and then process B, and so on, and so on, and so on, and so on.

FIG. 9 is a diagram showing another embodiment. Here, the same reference numerals as in FIG. 1 indicate the same parts.

8 is an edge detection circuit that detects edges using a known method such as Laplacian. The same processing as shown in FIG. 1 is performed on the portion determined to be an edge portion by the edge detection circuit 8. Therefore, since the character part is an edge part, it is possible to prevent white spots inside the character and to print the edges clearly.

In addition, by processing the portion determined to be a non-edge portion by the edge detection circuit 8 in a known error diffusion method circuit 9, it becomes possible to reproduce a halftone image satisfactorily.

〔effect〕

As explained above, having a two-stage binarization circuit has the effect of enhancing edges and preventing black parts inside characters from appearing white.

[Brief explanation of the drawing]

Fig. 1 is a block diagram showing an embodiment of the present invention, Fig. 2 is a block diagram showing details of the first binarization circuit, Fig. 3 is a layout diagram of the pixel of interest and surrounding pixels, and Fig. 4 is a block diagram showing the details of the first binarization circuit. FIG. 5 is a block diagram showing details of the error correction circuit, FIG. 5 is a block diagram showing details of the second binarization circuit, FIG. 6 is a diagram showing the error buffer memory, and FIG. 7 is an example of input data. FIG. 8 is a block diagram of a partially modified error correction circuit, and FIG. 9 is a diagram showing another embodiment. In the figure, 1 is a human power sensor, 2 is an A/D converter, 3 is a correction circuit, 4 is an error correction circuit, 5 is a first binarization circuit, and 6 is a second
, 7 is a printer, 8 is an edge detection circuit, 9 is a binarization circuit, and 7 is a printer.
is an error diffusion circuit.

Claims (1)

[Claims] A first binarization circuit determines whether the density data of the image is black or white, outputs an inverted signal thereof, and performs weighting based on the inverted signal and the density data around the pixel of interest. An image processing method characterized in that the number is calculated, added to the density data of the pixel of interest, and then binarized by a second binarization circuit.