Image processing apparatus, image forming apparatus, image processing method, and computer readable recording medium

• US 8,259,357 B2
• Filed: 03/07/2008
• Issued: 09/04/2012
• Est. Priority Date: 03/09/2007
• Status: Active Grant

• Current Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Murakami, Yoshinori
• Primary Examiner(s): Lett, Thomas
• Assistant Examiner(s): BURLESON, MICHAEL L
• Application Number:
  US12/044,608
• Publication Number:
  US 20080218803A1
• Time in Patent Office: 1,642 Days
• Field of Search: 358/3.1, 358/3.15, 358/2.1, 358/1.6, 358/1.9, 358/448, 382/266
• US Class Current: 358/3.01
• CPC Class Codes: H04N 1/4051 producing a dispersed dots halftone pattern, the dots having substantially the same size different sizes H04N1/4057
• CPC Class Codes: H04N 1/4052 by error diffusion, i.e. transferring the binarising error to neighbouring dot decisions
• CPC Class Codes: H04N 1/4092 Edge or detail enhancement

Abstract

An error diffusion process section performs an error diffusion process on a pixel value of each of processing object pixels and outputs the processed pixel value to an output selection section. A blue noise mask process performs a blue noise mask process on a pixel value of each of processing object pixels and outputs the processed pixel value to the output selection section. The output selection section selects and outputs the pixel value outputted from the error diffusion process section when a segmentation class signal indicates a character (text) area or a halftone dot area, namely an edge area, and selects and outputs the pixel value outputted from the blue noise mask process section when a segmentation class signal indicates an area other than the character area or the halftone dot area, namely non-edge area.

Claims

1. An image processing apparatus comprising:

a segmentation process section, which performs classification processing for an object pixel based on a pixel surrounding the object pixel, for classifying whether each of pixels forming inputted image data belongs to at least an edge area or a non-edge area; and

a tone reproduction process section for converting the inputted image data into an image data with a predetermined gray level and outputting the converted image data,

the tone reproduction process section including;

an error diffusion process section for performing conversion of gray level using an error diffusion method;

a blue noise mask process section for performing conversion of the gray level using a blue noise mask method; and

an output selection section for outputting a gray level value converted by the error diffusion process section in the case in which the object pixel belongs to the edge area, and outputting a gray level value converted by the blue noise mask process section in the case in which the pixel belongs to the non-edge area.

2. The image processing apparatus of claim 1, wherein the error diffusion process is performed using a set of error diffusion coefficients.

3. The image processing apparatus of claim 1, wherein the pixels to which the error is diffused based on the error diffusion coefficient are, related to the object pixel, an unprocessed next pixel, a pixel in the same position on the next line, and pixels on both of left and right sides of the pixel in the same position on the next line.

4. The image processing apparatus of claim 1, wherein the pixels to which the error is diffused based on the error diffusion coefficient are, related to the object pixel, an unprocessed next pixel and a pixel in the same position on the next line.

5. The image processing apparatus of claim 1, wherein the pixel to which the error is diffused based on the error diffusion coefficient is an unprocessed next pixel related to the object pixel.

6. The image processing apparatus of claim 1, wherein each of the pixels includes a plurality of color components, and

the tone reproduction process section performs conversion of the gray level for each of the color components, and selects the threshold mask for each of the color components.

7. An image forming apparatus comprising:

an image input apparatus for inputting image data to an image processing apparatus;

the image processing apparatus of claim 1; and

an image output apparatus for forming an image based on the image data with a gray level converted by the image processing apparatus.

8. An image processing apparatus comprising:

a segmentation process section, which performs classification processing for an object pixel based on a pixel surrounding the object pixel, for classifying whether each of pixels forming inputted image data belongs to at least an edge area or a non-edge area; and

a tone reproduction process section for converting the inputted image data into an image data with a predetermined gray level and outputting the converted image data,

wherein the tone reproduction section performs the conversion of the gray level using an error diffusion method, and

selects a fixed threshold value in the case in which the object pixel belongs to the edge area, and selects a threshold value corresponding to a position of the object pixel from a threshold mask to quantize a gray level value by a threshold process using the selected threshold value.

9. The image processing apparatus of claim 8, wherein the tone reproduction process section stores an error diffusion coefficient for the edge area and an error diffusion coefficient for the non-edge area, and

selects the error diffusion coefficient for the edge area in the case in which the object pixel belongs to the edge section, selects the error diffusion coefficient for the non-edge area in the case in which the pixel belongs to the non-edge section, and calculates the diffusion error using the selected error diffusion coefficient.

10. The image processing apparatus of claim 9, wherein the tone reproduction process section does not substantially carry out the error diffusion by the error diffusion method in the case in which the object pixel belongs to the non-edge area.

11. The image processing apparatus of claim 8, wherein the error diffusion process is performed using a set of error diffusion coefficients.

12. The image processing apparatus of claim 8, wherein the pixels to which the error is diffused based on the error diffusion coefficient are, related to the object pixel, an unprocessed next pixel, a pixel in the same position on the next line, and pixels on both of left and right sides of the pixel in the same position on the next line.

13. The image processing apparatus of claim 8, wherein the pixels to which the error is diffused based on the error diffusion coefficient are, related to the object pixel, an unprocessed next pixel and a pixel in the same position on the next line.

14. The image processing apparatus of claim 8, wherein the pixel to which the error is diffused based on the error diffusion coefficient is an unprocessed next pixel related to the object pixel.

15. The image processing apparatus of claim 8, wherein each of the pixels includes a plurality of color components, and

the tone reproduction process section performs conversion of the gray level for each of the color components, and selects the threshold mask for each of the color components.

16. An image forming apparatus comprising:

an image input apparatus for inputting image data to an image processing apparatus;

the image processing apparatus of claim 8; and

an image output apparatus for forming an image based on the image data with a gray level converted by the image processing apparatus.

17. An image processing method comprising:

a segmentation process step of performing classification processing for an object pixel based on a pixel surrounding the object pixel, and classifying whether each of pixels forming inputted image data belongs to at least an edge area or a non-edge area; and

a tone reproduction process step of converting the inputted image data into an image data with a predetermined gray-scale and outputting the converted image data,

wherein in the tone reproduction process step, the conversion of the gray-scale is performed by the error diffusion method in the case in which the processing object pixel belongs to the edge area, and the conversion of the gray-scale is performed by the blue noise mask method in the case in which the pixel belongs to the non-edge area.

18. A computer readable recording medium recording an image processing program for making a computer execute the image processing method of claim 17.

19. An image processing method comprising:

a segmentation process step of performing classification processing for an object pixel based on a pixel surrounding the object pixel, and classifying whether each of pixels forming inputted image data belongs to at least an edge area or a non-edge area; and

a tone reproduction process step of converting the inputted image data into an image data with a predetermined gray-scale and outputting the converted image data,

the tone reproduction process step including;

a selection step of selecting a fixed threshold value in the case in which a processing the object pixel belongs to the edge area, and selecting a threshold value corresponding to a position of the processing object pixel from a threshold mask;

a quantization step of quantizing the gray-scale value by a threshold process using the selected threshold value; and

an error diffusion step of performing the error diffusion using the error diffusing method.

20. A computer readable recording medium recording an image processing program for making a computer execute the image processing method of claim 19.