Image processing apparatus, image forming apparatus, image reading process apparatus, image processing method, image processing program, and computer-readable storage medium

• US 20060152765A1
• Filed: 01/10/2006
• Published: 07/13/2006
• Est. Priority Date: 01/11/2005
• Status: Abandoned Application

• Current Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Adachi, Yasushi
• Application Number:
  US11/328,088
• Publication Number:
  US 20060152765A1
• Time in Patent Office: Days
• US Class Current: 358/3.60
• CPC Class Codes: H04N 1/403 Discrimination between the two tones in the picture signal of a two-tone original
• CPC Class Codes: H04N 1/405 Halftoning, i.e. converting the picture signal of a continuous-tone original into a corresponding signal showing only two levels

Abstract

The halftone frequency determining section is provided with a flat halftone discriminating section for extracting information of density distribution per segment block, and discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high; a threshold value setting section for setting a threshold value for use in binarization; a binarization section for performing the binarization in order to generate binary data of each pixel in the segment block according to the threshold value; a transition number calculating section for calculating out transition numbers of the binary data; and a maximum transition number averaging section for averaging the transition numbers which are of the segment block discriminated as the flat halftone region by the flat halftone discriminating section, and which are calculated out by a maximum transition number calculating section. A halftone frequency is determined (i.e., found out) based on only the maximum transition number average of the segment block discriminated as the flat halftone region. With this, it is possible to provide an image processing apparatus that can determine the halftone frequency highly accurately.

Claims

1. An image processing apparatus comprising:

halftone frequency determining means for determining a halftone frequency of an inputted image, the halftone frequency determining means comprising;

flat halftone discriminating means for extracting information of density distribution per segment block consisting of a plurality of pixels, and discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high;

extracting means for extracting a feature of density transition between pixels of the segment block which the flat halftone discriminating means discriminates as the flat halftone region; and

halftone frequency estimating means for estimating the halftone frequency, based on the feature extracted by the extracting means.

2. An image processing apparatus as set forth in claim 1, wherein:

the extracting means comprises;

threshold value setting means for setting a threshold value for use in binarization;

binarization means for performing the binarization in order to generate binary data of each pixel in the segment block according to the threshold value set by the threshold value setting means;

transition number calculating means for calculating out transition numbers of the binary data generated by the binarization means; and

transition number extracting means for extracting, as the feature, a transition number of that segment block which the flat halftone discriminating means discriminates as the flat halftone region, from among the transition numbers calculated out by the transition number calculating means.

3. An image processing apparatus as set forth in claim 1, wherein:

the extracting means comprises;

threshold value setting means for setting a threshold value for use in binarization;

binarization means for performing the binarization in order to generate, according to the threshold value set by the threshold value setting means, binarization data of each pixel in the segment block that the flat halftone discriminating means discriminates as the flat halftone region; and

transition number calculating means for calculating out, as the feature, a transition number of the binary data generated by the binarization means.

4. An image processing apparatus as set forth in claim 2, wherein:

the threshold value set by the threshold value setting means is an average density of the pixels in the segment block.

5. An image processing apparatus as set forth in claim 3, wherein:

the threshold value set by the threshold value setting means is an average density of the pixels in the segment block.

6. An image processing apparatus as set forth in claim 1, wherein:

the flat halftone discriminating means performs the discrimination whether the segment block is the flat halftone region or not based on density differences between adjacent pixels in the segment block.

7. An image processing apparatus as set forth in claim 1, wherein:

the segment block is partitioned into a predetermined number of sub segment blocks; and

the flat halftone discriminating means finds average densities of pixels in the sub segment blocks, and performs the discrimination whether the segment block is the flat halftone region or not based on a difference(s) between the average densities of the sub segment blocks.

8. An image forming apparatus comprising:

an image processing apparatus comprising;

halftone frequency determining means for determining a halftone frequency of an inputted image,

the halftone frequency determining means comprising;

flat halftone discriminating means for extracting information of density distribution per segment block consisting of a plurality of pixels, and discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high;

extracting means for extracting a feature of density transition between pixels of the segment block which the flat halftone discriminating means discriminates as the flat halftone region; and

halftone frequency estimating means for estimating the halftone frequency, based on the feature extracted by the extracting means.

9. An image reading process apparatus comprising:

an image processing apparatus comprising;

halftone frequency determining means for determining a halftone frequency of an inputted image,

the halftone frequency determining means comprising;

flat halftone discriminating means for extracting information of density distribution per segment block consisting of a plurality of pixels, and discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high; and

extracting means for extracting a feature of density transition between pixels of the segment block which the flat halftone discriminating means discriminates as the flat halftone region; and

halftone frequency estimating means for estimating the halftone frequency, based on the feature extracted by the extracting means.

10. An image processing method comprising:

determining a halftone frequency of an inputted image,

the step of determining the halftone frequency comprising;

discriminating a flat halftone, the step of discriminating including (a) extracting information of density distribution per segment block consisting of a plurality of pixels, and (b) discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high; and

extracting a feature of density transition between pixels of the segment block which is discriminated as the flat halftone region; and

estimating the halftone frequency, based on the feature extracted.

11. An image processing method as set forth in claim 10, wherein:

the step of extracting comprising;

setting a threshold value for use in binarization;

performing the binarization in order to generate binary data of each pixel in the segment block according to the set threshold value;

calculating out transition numbers of the binary data; and

extracting, as the feature, a transition number of that segment block which the step of discriminating discriminates as the flat halftone region, from among the transition numbers calculated out.

12. An image processing method as set forth in claim 10, wherein:

the step of extracting comprising;

setting a threshold value for use in binarization for the segment block that the step of discriminating discriminates as the flat halftone region;

performing the binarization in order to generate, according to the set threshold value, binarization data of each pixel in the segment block that the step of discriminating discriminates as the flat halftone region; and

calculating out, as the feature, a transition number of the binary data.

13. An image processing method as set forth in claim 11, wherein:

the threshold value set in the step of setting is an average density of the pixels in the segment block.

14. An image processing method as set forth in claim 12, wherein:

the threshold value set in the step of setting is an average density of the pixels in the segment block.

15. An image processing method as set forth in claim 10, wherein:

in the step of discriminating, the discrimination whether the segment block is the flat halftone region or not is performed based on density differences between adjacent pixels in the segment block.

16. An image processing method as set forth in claim 10, wherein:

the segment block is partitioned into a predetermined number of sub segment blocks; and

the discrimination whether the segment block is the flat halftone region or not is performed based on a difference(s) between average densities of the sub segment blocks in the step of discriminating.

17. An image processing program for operating an image processing apparatus comprising halftone frequency determining means for determining a halftone frequency of an inputted image,

the halftone frequency determining means comprising:

flat halftone discriminating means for extracting information of density distribution per segment block consisting of a plurality of pixels, and discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high;

extracting means for extracting a feature of density transition between pixels of the segment block which the flat halftone discriminating means discriminates as the flat halftone region; and

halftone frequency estimating means for estimating the halftone frequency, based on the feature extracted by the extracting means, and

the program causing a computer to serve as each means.

18. A computer-readable recording medium in which an image processing program for operating an image processing apparatus comprising halftone frequency determining means for determining a halftone frequency of an inputted image is stored,

the halftone frequency determining means comprising:

flat halftone discriminating means for extracting information of density distribution per segment block consisting of a plurality of pixels, and discriminating, based on the information of density distribution, whether the segment block is a flat halftone region in which density transition is low or of a non-flat halftone region in which the density transition is high;

extracting means for extracting a feature of density transition between pixels of the segment block which the flat halftone discriminating means discriminates as the flat halftone region; and

halftone frequency estimating means for estimating the halftone frequency, based on the feature extracted by the extracting means, and

the program causing a computer to serve as each means.