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A Novel Approach To Image Thresholding Based On 2d Homogeneity Histogram And Maximum Fuzzy Entropy

Author

Listed:
  • H. D. CHENG

    (School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China;
    Department of Computer Science, Utah State University, Logan, UT 84322, USA)

  • YANHUI GUO

    (Department of Computer Science, Utah State University, Logan, UT 84322, USA)

  • YINGTAO ZHANG

    (School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China)

Abstract

Image thresholding is an important topic for image processing, pattern recognition and computer vision. Fuzzy set theory has been successfully applied to many areas, and it is generally believed that image processing bears some fuzziness in nature. In this paper, we employ the newly proposed 2D homogeneity histogram (homogram) and the maximum fuzzy entropy principle to perform thresholding. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively. Especially, it not only can process "clean" images, but also can process images with different kinds of noises and images with multiple kinds of noise well without knowing the type of the noise, which is the most difficult task for image thresholding. It will be useful for applications in computer vision and image processing.

Suggested Citation

  • H. D. Cheng & Yanhui Guo & Yingtao Zhang, 2011. "A Novel Approach To Image Thresholding Based On 2d Homogeneity Histogram And Maximum Fuzzy Entropy," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 7(01), pages 105-133.
    • Handle: RePEc:wsi:nmncxx:v:07:y:2011:i:01:n:s1793005711001834
    DOI: 10.1142/S1793005711001834
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