Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.322
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.
Feature divergence; fuzzy dissimilarity; color image segmentation
Zhang Baoliang, Lei Lihua, Zhang Li, Cai Zhenjiang, Li Dongming, Liu Yaju, "Research on Image Segmentation Based on Fuzzy Theory", Computer Science and Information Engineering, World Congress on, vol. 04, no. , pp. 790-794, 2009, doi:10.1109/CSIE.2009.322