Fuzzy Possibilistic C-Means Clustering Algorithm for Content Based Image Retrieval

With the development of the Internet and the availability of image capturing devices such as digital cameras, image scanners, and the size of digital image collection is increasing rapidly and hence there is a huge demand for effective image retrieval system. For better image retrieval, content-based image retrieval (CBIR) was introduced. In CBIR, images are indexed by their visual content, such as color, texture, shapes. Further research has suggested the usage of clustering technique of image retrieval. Clustered images are utilized by Content-Based Image Retrieval (CBIR) and querying system that requires effective query matching in large image database. For improving the performance of image retrieval, this paper focuses on using the fuzzy based clustering algorithm. Particularly, this paper uses Fuzzy Possibilistic C-Means (FPCM) clustering algorithm for retrieving the most similar images. The main intention of using the FPCM clustering is its combinational advantage of both fuzzy and possibilistic approaches. Experimental result suggests that the proposed image retrieval technique results in better retrieval.