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2009 WRI World Congress on Computer Science and Information Engineering
Research on Image Segmentation Based on Fuzzy Theory
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
Image segmentation is one of the key steps in image analysis, where the fuzzy theory based methods are widely used,but, none had universally property to segment all types color images. So, to improve segmentation quality and universally property of segmentation algorithm, a new fuzzy color image segmentation algorithm was brought out based on feature divergence and fuzzy dissimilarity. The algorithm measured the otherness of two stylebooks space eigenvector by feature divergence, and extracted sub-images feature eigenvector using watershed algorithm, depressed operation data number. Combination of sub-image was done by dint of fuzzy dissimilarity and morphological theory, and the isolated points were eliminated, and made color image segmentation more according with the human segmentation strategy. The method efficiency and feasibility were confirmed by experimental results.
Index Terms:
Feature divergence; fuzzy dissimilarity; color image segmentation
Liu Yaju, Zhang Baoliang, Zhang Li, Li Dongming, Cai Zhenjiang, Lei Lihua, "Research on Image Segmentation Based on Fuzzy Theory," csie, vol. 4, pp.790-794, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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