Image processing method, image processing apparatus, image reading apparatus, image forming apparatus, program, and storage medium

• US 20070058211A1
• Filed: 09/13/2006
• Published: 03/15/2007
• Est. Priority Date: 09/14/2005
• 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: Kubota, Kazuhisa
• Granted Patent: US 7,791,764 B2
• Time in Patent Office: Days
• US Class Current: 358/462
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables
• CPC Class Codes: H04N 1/40062 Discrimination between different image types, e.g. two-tone, continuous tone

Abstract

An image processing apparatus includes an automatic document type discrimination section for estimating a type of input image data. The automatic document type discrimination section is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, and the automatic document type discrimination section estimates the type of the image data. Therefore, the image processing apparatus can exactly estimate the type of the image.

Claims

1. An image processing apparatus, comprising discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

2. An image reading apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

3. An image forming apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

4. A program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, and the discrimination means estimates the type of the image data on the basis of a result of the detection,

said program causing a computer to function as the discrimination means.

5. A computer-readable storage medium for storing a program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, and the discrimination means estimates the type of the image data on the basis of a result of the detection,

said program causing a computer to function as the discrimination means.

6. An image processing apparatus, comprising discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using a threshold value, regarding same characteristics, which is set with respect to each of the plural types of halftone dot areas, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

7. The image processing apparatus as set forth in claim 6, wherein

the discrimination means includes:

a characteristic extracting section for extracting a characteristic regarding each of the plural types of halftone dot areas from the image data;

a threshold value setting section for setting (i) a first threshold value regarding the characteristic and (ii) a second threshold value regarding the characteristic and being more unconfined than the first threshold value;

a first halftone dot pixel detection section for comparing the characteristic extracted by the characteristic extracting section with the first threshold value so as to detect first halftone dot pixels from the image data;

a second halftone dot pixel detection section for comparing the characteristic extracted by the characteristic extracting section with the second threshold value so as to detect second halftone dot pixels from the image data; and

a type determination section for determining a type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels in the image data.

8. The image processing apparatus as set forth in claim 7, wherein

the second halftone dot pixel detection section includes a judgment result correction section for correcting a result of judgment regarding a pixel judged, by the second threshold value, not to belong to the second halftone dot pixels, the correction being performed on the basis of a result of judgment regarding pixels existing around the pixel.

9. The image processing apparatus as set forth in claim 7, wherein the characteristic is obtained by extracting, from the image data, (i) density differences and (ii) busyness indicative of total sum of the density differences between adjacent pixels.

10. The image processing apparatus as set forth in claim 7, wherein the type determination section determines the type of image data on the basis of a ratio of the first halftone dot pixels to the second halftone dot pixels.

11. The image processing apparatus as set forth in claim 7, wherein

the first halftone dot pixels are halftone dot pixels belonging to a halftone printing picture area, the second halftone dot pixels include at least one of (i) the halftone dot pixels which belong to the halftone printing picture area and (ii) third halftone dot pixels which belong to neither the halftone printing picture area nor a photographic-picture area, and

the type determination section judges whether the third halftone dot pixels exist or not in the image data when the type of the image data is determined.

12. The image processing apparatus as set forth in claim 11, wherein:

when the type determination section of the discrimination means estimates that the image data includes the third halftone dot pixels, a single process is performed with respect to a whole area of the image data.

13. An image reading apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using a threshold value, regarding same characteristics, which is set with respect to each of the plural types of halftone dot areas, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

14. An image forming apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using a threshold value, regarding same characteristics, which is set with respect to each of the plural types of halftone dot areas, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

15. A program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using a threshold value, regarding same characteristics, which is set with respect to each of the plural types of halftone dot areas, and the discrimination means estimates the type of the image data on the basis of a result of the detection,

said program causing a computer to function as the discrimination means.

16. A computer-readable storage medium for storing a program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using a threshold value, regarding same characteristics, which is set with respect to each of the plural types of halftone dot areas, and the discrimination means estimates the type of the image data on the basis of a result of the detection,

said program causing a computer to function as the discrimination means.

17. An image processing apparatus, comprising discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using threshold values which are set with respect to the plural types of halftone dot areas respectively and which differ from each other so as to correspond to at least two types of halftone dot areas respectively, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

18. The image reading apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using threshold values which are set with respect to the plural types of halftone dot areas respectively and which differ from each other so as to correspond to at least two types of halftone dot areas respectively, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

19. The image forming apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using threshold values which are set with respect to the plural types of halftone dot areas respectively and which differ from each other so as to correspond to at least two types of halftone dot areas respectively, and the discrimination means estimates the type of the image data on the basis of a result of the detection.

20. A program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using threshold values which are set with respect to the plural types of halftone dot areas respectively and which differ from each other so as to correspond to at least two types of halftone dot areas respectively, and the discrimination means estimates the type of the image data on the basis of a result of the detection,

said program causing a computer to function as the discrimination means.

21. A computer-readable storage medium for storing a program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means is capable of detecting whether each of plural types of halftone dot areas exists or not in the image data, by using threshold values which are set with respect to the plural types of halftone dot areas respectively and which differ from each other so as to correspond to at least two types of halftone dot areas respectively, and the discrimination means estimates the type of the image data on the basis of a result of the detection,

said program causing a computer to function as the discrimination means.

22. An image processing apparatus, comprising discrimination means for estimating a type of input image data, wherein

the discrimination means includes:

a halftone dot pixel detection section for extracting, from the image data, a first characteristic regarding halftone dot pixels including first halftone dot pixels and second halftone dot pixels, and for detecting the halftone dot pixels from the image data on the basis of the first characteristic;

a first halftone dot pixel detection section for extracting a second characteristic, regarding the halftone dot pixels, which is different from the first characteristic, and for detecting the first halftone dot pixels from the halftone dot pixels on the basis of the second characteristic; and

a type determination section for calculating the number of the second halftone dot pixels from the number of the halftone dot pixels and the number of the first halftone dot pixels, and for determining the type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels.

23. The image processing apparatus as set forth in claim 22, wherein the first characteristic is obtained by extracting, from the image data, (i) density differences and (ii) busyness indicative of total sum of the density differences between adjacent pixels.

24. The image processing apparatus as set forth in claim 22, wherein the second characteristic is the number of image density transition in a block having a plurality of pixels and centering a current pixel.

25. The image processing apparatus as set forth in claim 22, wherein the second characteristic is a standard deviation of pixel values in a block having a plurality of pixels and centering a current pixel.

26. The image processing apparatus as set forth in claim 22, wherein the second characteristic is an average density difference of a block having a plurality of pixels and centering a current pixel.

27. The image processing apparatus as set forth in claim 22, wherein the type determination section determines the type of the image data on the basis of a ratio of the first halftone dot pixels to the second halftone dot pixels.

28. The image processing apparatus as set forth in claim 22, wherein the first halftone dot pixels are halftone dot pixels belonging to a halftone printing picture area, the second halftone dot pixels include at least one of (i) the halftone dot pixels which belong to the halftone printing picture area and (ii) third halftone dot pixels which belong to neither the halftone printing picture area nor a photographic-picture area, and

the type determination section judges whether the third halftone dot pixels exist or not in the image data when the type of the image data is determined.

29. The image processing apparatus as set forth in claim 28, wherein:

when the type determination section of the discrimination means determines that the image data includes the third halftone dot pixels, a single process is performed with respect to a whole area of the image data.

30. An image reading apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means includes:

a halftone dot pixel detection section for extracting, from the image data, a first characteristic regarding halftone dot pixels including first halftone dot pixels and second halftone dot pixels, and for detecting the halftone dot pixels from the image data on the basis of the first characteristic;

a first halftone dot pixel detection section for extracting a second characteristic, regarding the halftone dot pixels, which is different from the first characteristic, and for detecting the first halftone dot pixels from the halftone dot pixels on the basis of the second characteristic; and

a type determination section for calculating the number of the second halftone dot pixels from the number of the halftone dot pixels and the number of the first halftone dot pixels, and for determining the type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels.

31. An image forming apparatus, comprising an image processing apparatus which includes discrimination means for estimating a type of input image data, wherein

the discrimination means includes:

a halftone dot pixel detection section for extracting, from the image data, a first characteristic regarding halftone dot pixels including first halftone dot pixels and second halftone dot pixels, and for detecting the halftone dot pixels from the image data on the basis of the first characteristic;

a first halftone dot pixel detection section for extracting a second characteristic, regarding the halftone dot pixels, which is different from the first characteristic, and for detecting the first halftone dot pixels from the halftone dot pixels on the basis of the second characteristic; and

a type determination section for calculating the number of the second halftone dot pixels from the number of the halftone dot pixels and the number of the first halftone dot pixels, and for determining the type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels.

32. A program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein

the discrimination means includes:

a halftone dot pixel detection section for extracting, from the image data, a first characteristic regarding halftone dot pixels including first halftone dot pixels and second halftone dot pixels, and for detecting the halftone dot pixels from the image data on the basis of the first characteristic;

a first halftone dot pixel detection section for extracting a second characteristic, regarding the halftone dot pixels, which is different from the first characteristic, and for detecting the first halftone dot pixels from the halftone dot pixels on the basis of the second characteristic; and

a type determination section for calculating the number of the second halftone dot pixels from the number of the halftone dot pixels and the number of the first halftone dot pixels, and for determining the type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels,

said program causing a computer to function as the discrimination means.

33. A computer-readable storage medium for storing a program for causing an image processing apparatus to operate, said image processing apparatus including discrimination means for estimating a type of input image data, wherein `the discrimination means includes:

a halftone dot pixel detection section for extracting, from the image data, a first characteristic regarding halftone dot pixels including first halftone dot pixels and second halftone dot pixels, and for detecting the halftone dot pixels from the image data on the basis of the first characteristic;

a first halftone dot pixel detection section for extracting a second characteristic, regarding the halftone dot pixels, which is different from the first characteristic, and for detecting the first halftone dot pixels from the halftone dot pixels on the basis of the second characteristic; and

a type determination section for calculating the number of the second halftone dot pixels from the number of the halftone dot pixels and the number of the first halftone dot pixels, and for determining the type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels, `said program causing a computer to function as the discrimination means.

34. A method for processing an image, comprising the step of judging a type of input image data, wherein

in the step, it is detected whether each of plural types of halftone dot areas exists or not in the image data, and the type of the image data is judged on the basis of a result of the detection.

35. A method for processing an image, comprising the step of judging a type of input image data, wherein

in the step, it is detected whether plural types of halftone dot areas exist or not in the image data on the basis of a threshold value, regarding same characteristics, which is set with respect to each of the plural types of halftone dot areas, and the type of the image data is judged on the basis of a result of the detection.

36. A method for processing an image, comprising the step of judging a type of input image data, wherein

in the step, it is detected whether each of plural types of halftone dot areas exists or not in the image data on the basis of threshold values which are set with respect to the plural types of halftone dot areas respectively and which differ from each other so as to correspond to at least two types of halftone dot areas respectively, and the type of the image data is judged on the basis of a result of the detection.

37. A method for processing an image, comprising the step of judging a type of input image data, wherein

said step includes the sub-steps of:

extracting, from the image data, a first characteristic regarding halftone dot pixels including first halftone dot pixels and second halftone dot pixels, and detecting the halftone dot pixels from the image data on the basis of the first characteristic;

extracting a second characteristic, regarding the halftone dot pixels, which is different from the first characteristic, and detecting the first halftone dot pixels from the halftone dot pixels on the basis of the second characteristic; and

calculating the number of the second halftone dot pixels from the number of the halftone dot pixels and the number of the first halftone dot pixels, and determining the type of the image data on the basis of the number of the first halftone dot pixels and the number of the second halftone dot pixels.

[EQUATION 1]

$\begin{array}{cc}{\mathrm{\sigma <br><br>}}^2=\frac{1}{n}<br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>{\left(\mathrm{Pi}-\stackrel{\_}{P}\right)}^2<br><br><br><br>n<br><br>\text{;<br><br>}<br><br>\mathrm{NUMBER}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{OF}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{PIXELS}<br><br><br><br>\mathrm{Pi}<br><br>\text{;<br><br>}<br><br>\mathrm{PIXEL}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{VALUE}<br><br><br><br>\stackrel{\_}{P}<br><br>\text{;<br><br>}<br><br>\mathrm{AVERAGE}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{VALUE}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{OF}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{PIXEL}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{VALUES}<br><br>\text{\hspace{1em}<br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{IN}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{BLOCK}& \left(1\right)\end{array}$

TABLE 1NUMBEREDGE-DETECTIONOF DENSITYFILTERTRANSITIONJUDGMENT10TEXT01HALFTONE DOT PIXEL11HALFTONE DOT PIXEL00UNKNOWN