A Fuzzy Clustering Approach for Complex Color Image Segmentation Based on Gaussian Model with Interactions between Color Planes and Mixture Gaussian Model

2017 ◽  
Vol 20 (1) ◽  
pp. 309-317 ◽  
Author(s):  
Xuemei Zhao ◽  
Yu Li ◽  
Quanhua Zhao
2013 ◽  
Vol 380-384 ◽  
pp. 3469-3473
Author(s):  
Xiao Feng Wang ◽  
Jian Hua Li

As next generation of the web, the semantic web aims at a more intelligent web severing machines as well as people, based on radical notions of information sharing and acquisition. For color image segmentation, semantic color is our focus. One method of color partition is fuzzy clustering which has been widely used in image segmentation. However, the fuzzy clustering algorithm is parameter sensitive, and lack of availability because of its initial focus on physical features. To improve the above problems, a novel fuzzy clustering method based on semantic color retrieval for image segmentation is proposed in this paper. The method is realized by modifying the membership function in the conventional clustering algorithm and by constructing the semantic color retrieval mechanism to achieve the semantic color extraction, which take human visual subjectivity into account in semantics. Experimental results show that the presented method performs more effectively than the previous algorithm.


2013 ◽  
Vol 13 (4) ◽  
pp. 2017-2036 ◽  
Author(s):  
Khang Siang Tan ◽  
Nor Ashidi Mat Isa ◽  
Wei Hong Lim

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