Fuzzy distinction based thresholding technique for image segmentation

• US 6,625,308 B1
• Filed: 09/10/1999
• Issued: 09/23/2003
• Est. Priority Date: 09/10/1999
• Status: Expired due to Fees

• Current Assignee: Indian Institute of Technology Bombay, Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Rao, A. K. V. Subba, Acharya, Tinku, Ray, Ajay K.
• Primary Examiner(s): Johns, Andrew W.
• Assistant Examiner(s): Alavi, Amir
• Application Number:
  US09/393,017
• Time in Patent Office: 1,474 Days
• Field of Search: 382/162, 382/164, 382/168, 382/170, 382/171, 706/8, 706/14, 706/900
• US Class Current: 382/168
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/143 involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06V 10/28 Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
• CPC Class Codes: Y10S 706/90 Fuzzy logic

Abstract

Embodiments of a fuzzy distinction based thresholding technique for image segmentation are disclosed. In one embodiment, at least one signal value level of the image is determined along which to divide a fuzzy histogram, the histogram being based, at least in part, on the image. The signal value represents a value which produces a divided fuzzy histogram with an extreme value of one of distinctiveness and fuzziness based on a measure of multidimensional distance between measurement distributions and their respective complements. The image is then segmented using the at least one signal value.

Claims

1. A method of segmenting a image comprising:

determining at least one signal value level of the potential signal value levels of the image along which to divide a fuzzy histogram into at least two measurement distributions, the histogram being based, at least in part, on the image, the at least one signal value level being the at least one of the potential signal value levels that produces a divided fuzzy histogram having, based on a measure of the multidimensional distance between each of the measurement distributions and their respective complements, an extreme value of one of distinctiveness and fuzziness; and

segmenting the image using the at least one signal value level.

2. The method of claim 1, wherein the image comprises a digital image having digital pixel signal value levels at each pixel location of the digital image.

3. The method of claim 2, wherein the digital pixel signal values each comprise a plurality of bits.

4. The method of claim 3, wherein the plurality of bits comprises eight bits.

5. The method of claims 3, wherein the digital image comprises a gray scale digital image and the digital signal pixel value levels of the digital image comprise gray scale digital signal value levels.

6. The method of claim 3, wherein the digital image comprises a color digital image, and wherein the color space format of the color digital image comprises a three-color plane color space format.

7. The method of claim 6, wherein determining the digital pixel signal value level comprises determining the digital pixel signal value level based, at least in part, on all three color space planes of the digital image.

8. The method of claim 7, wherein segmenting the digital image comprises segmenting all three color space planes of the digital image.

9. The method of claim 6, wherein determining the digital pixel signal value level comprises determining the digital pixel signal value level based, at least in part, on at least any one of the color space planes of the digital image.

10. The method of claim 9, wherein segmenting the digital image comprises segmenting all three color-space planes of the digital image.

11. The method of claim 9, wherein determining the digital pixel signal value level comprises determining the digital pixel signal value level based, at least in part, on only one of the color space planes of the digital image.

12. The method of claim 11, wherein segmenting the digital image comprises segmenting all three color space planes of the digital image.

13. The method of claim 3, wherein the color space format of the color digital image comprises the YUV color space format.

14. The method of claim 3, wherein the color space format of the color digital image comprises the RGB color space format.

15. The method of claim 3, wherein determining the at least one digital pixel signal value along which to divide the fuzzy histogram comprises determining more than one digital pixel signal value along which to divide the fuzzy histogram.

16. The method of claim 15, wherein determining more than one digital pixel signal value along which to divide the fuzzy histogram comprises determining two digital pixel signal values along which to divide the fuzzy histogram.

17. The method of claim 15, wherein determining more than one digital pixel signal value along which to divide the fuzzy histogram comprises determining three digital pixel signal values along which to divide the fuzzy histogram.

18. The method of claim 3, and further comprising:

determining at least one digital pixel signal value level along which to divide another fuzzy histogram, the another fuzzy histogram being based, at least in part, on one of the segmented portions of the digital image, the at least one digital pixel signal value level of the another fuzzy histogram being the at least one of the potential digital pixel signal value levels of the digital image that produces a divided another fuzzy histogram having the largest distinctiveness based on a measure of the multidimensional distance between each of the measurement distributions and their respective complements; and

segmenting the one of the segmented portions of the digital image using the at least one digital pixel signal value level.

19. The method of claim 1, wherein the at least one level of the potential signal values produces a divided fuzzy histogram having the greatest distinctiveness.

20. A method of segmenting an image comprising:

constructing a fuzzy histogram based, at least in part, on the signal value levels of the image, wherein the fuzzy histogram is divided into at least two measurement distributions along at least one of the potential signal value levels of the image;

computing one of the distinctiveness and the fuzziness for the divided fuzzy histogram using a measure of the multidimensional distance between each of the measurement distributions and their respective complements;

repeating the prior two operations, constructing and computing, for every potential signal value level of the image;

determining the at least one signal value level of the potential signal value levels that provides the divided fuzzy histogram with an extreme value of one of the distinctiveness and the fuzziness; and

segmenting the image using the at least one signal value level.

21. The method of claim 20, wherein the image comprises a digital image having digital pixel signal value levels at each pixel location of the digital image.

22. The method of claim 21, wherein the digital pixel signal values each comprise a plurality of bits.

23. The method of claim 22, and further comprising:

determining at least one digital pixel signal value level along which to divide another fuzzy histogram, the another fuzzy histogram being based, at least in part, on one of the segmented portions of the digital image, the at least one digital pixel signal value level of the another fuzzy histogram being the at least one of the potential digital pixel signal value levels of the digital image that produces a divided another fuzzy histogram having the largest distinctiveness based on a measure of multidimensional distance between each measurement distribution and its respective complement; and

segmenting the one of the segmented portions of the digital image using the at least one digital pixel signal value level.

24. An apparatus comprising:

a computing platform, said computing platform being adapted to segment an image;

said computing platform further including the capability to;

determine at least one signal value level of the potential signal value levels of the image along which to divide a fuzzy histogram, the fuzzy histogram being based, at least in part, on the image, to produce a divided fuzzy histogram, the at least one signal value level being the at least one of the potential signal value levels that produces a divided fuzzy histogram having the largest distinctiveness based on a measure of multidimensional distance; and

segment the image using the at least one signal value level.

25. The apparatus of claim 24, wherein said computing platform comprises at least one of a desktop personal computer, a laptop personal computer, and a server.

26. The apparatus of claim 24, wherein said computing platform is further adapted to segment a digital image having digital pixel signal value levels in each pixel location of the digital image.

27. The apparatus of claim 25, wherein the digital pixel signal values of the digital image each comprise a plurality of bits.

28. An article comprising:

a storage medium having stored thereon instructions that, when executed by a computing platform, result in the following operations by the computing platform to segment an image;

determining at least one signal value level of the potential signal value levels of the image along which to divide a fuzzy histogram, the fuzzy histogram being based, at least in part, on the image, to produce a divided fuzzy histogram, the at least one signal value level being the at least one of the potential signal value levels that produces a divided fuzzy histogram having an extreme based on a measure of multidimensional distance; and

segmenting the image using the at least one signal value level.

29. The article of claim 28, wherein said storage medium has stored thereon instructions that, when executed, further result in the computing platform segmenting a digital image having digital pixel signal value levels in each pixel location of the digital image.

30. The article of claim 29, wherein the digital pixel signal values of the digital image each comprise a plurality of bits.