NDLI: An algorithm based on rough-set theory for color image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Ming-Xin Zhang Cai-Yun Zhao Zhao-Wei Shang Hua Li Jin-Long Zheng
Copyright Year	2010
Description	Author affiliation: College of Computer Science, ChongQing University, Chongqing, 400030, China (Zhao-Wei Shang) \|\| College of Mathematics and Information Science, Northwest Normal University, Lanzhou 730070, China (Hua Li) \|\| School of Computer Science & Engineering, Changshu Institute of Technology, Changshu, 215500, China (Ming-Xin Zhang; Cai-Yun Zhao; Jin-Long Zheng)
Abstract	In view of the over- and under-segmentation problems existed in the conventional image segmentation based on rough-set theory, an novel color image segmentation approach based on Rough-Set theory is presented in this paper. Firstly, the new distance has been defined by using the vector angle and Euclidean distance. And then according to the new distance, the space binary matrixes that represent the similar color sphere and the Histon of each color component are calculated. Finally, the color image segmentation is implemented by selection of threshold values and region merging through introducing a histogram based on roughness. The analysis of experimental results show that the proposed approach yields better segmentation which is more intuitive to human vision compare with the conventional image segmentation based on rough-set theory.
Starting Page	28
Ending Page	32
File Size	218631
Page Count	5
File Format	PDF
ISBN	9781424465309
e-ISBN	9781424465316
DOI	10.1109/ICWAPR.2010.5576457
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Histograms Image color analysis Color Rough-set Pattern recognition Histon Approximation methods Pixel
Content Type	Text
Resource Type	Article

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