A NOVEL APPROACH TO IMAGE THRESHOLDING BASED ON 2D HOMOGENEITY HISTOGRAM AND MAXIMUM FUZZY ENTROPY

H. D. Cheng (), Yanhui Guo () and Yingtao Zhang ()
Additional contact information
H. D. Cheng: School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China;
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

New Mathematics and Natural Computation (NMNC), 2011, vol. 07, issue 01, 105-133

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.

Keywords: Image thresholding; homogeneity; 2D homogeneity histogram (homogram); maximum entropy principle (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S1793005711001834
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:nmncxx:v:07:y:2011:i:01:n:s1793005711001834

Ordering information: This journal article can be ordered from

DOI: 10.1142/S1793005711001834

Access Statistics for this article

New Mathematics and Natural Computation (NMNC) is currently edited by Paul P Wang

More articles in New Mathematics and Natural Computation (NMNC) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().