Title :
On Selecting an Optimal Number of Clusters for Color Image Segmentation
Author :
Le Capitaine, H. ; Frélicot, Carl
Author_Institution :
MIA Lab., Univ. of La Rochelle, La Rochelle, France
Abstract :
This paper addresses the problem of region-based color image segmentation using a fuzzy clustering algorithm, e.g. a spatial version of fuzzy c-means, in order to partition the image into clusters corresponding to homogeneous regions. We propose to determine the optimal number of clusters, and so the number of regions, by using a new cluster validity index computed on fuzzy partitions. Experimental results and comparison with other existing methods show the validity and the efficiency of the proposed method.
Keywords :
fuzzy set theory; image colour analysis; image segmentation; pattern clustering; fuzzy c-means; fuzzy clustering algorithm; fuzzy partitions; region-based color image segmentation; Clustering algorithms; Color; Image color analysis; Image segmentation; Indexes; Partitioning algorithms; Pixel; cluster validity; clustering methods; color image segmentation; overlap and separation measures;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.827