Color image segmentation using a new fuzzy clustering method

2005 ◽  
Author(s):  
N. Mezhoud ◽  
I. Merzoug ◽  
R. Boumaza ◽  
M.C. Batouche
Keyword(s):  
Image Segmentation ◽  
Fuzzy Clustering ◽  
Color Image ◽  
Color Image Segmentation ◽  
Clustering Method ◽  
Fuzzy Clustering Method

Semantic Color Retrieval of Color Image Based on Fuzzy Clustering

2013 ◽  
Vol 380-384 ◽  
pp. 3469-3473
Author(s):  
Xiao Feng Wang ◽  
Jian Hua Li
Keyword(s):  
Image Segmentation ◽  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Color Image ◽  
Color Image Segmentation ◽  
Fuzzy Clustering Method ◽  
Retrieval Mechanism ◽  
Previous Algorithm ◽  
Physical Features ◽  
Initial Focus

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.

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