A Comparative Analysis of Clustering Algorithms for Content Based Image Retrieval

Content based image retrieval is a set of techniques for retrieving semantically relevant images from an image data based on automatically derived image features. In CBIR, Image are indexed by their visual content, such as color, texture and shapes. Further research has suggested that the usage of clustering technique of image retrieval. For this paper we compare Fuzzy Possiblistic C-Means clustering algorithm for retrieving the most similar images. In our experimental results shows that the modify Fuzzy Possiblistic Clustering Algorithm is better retrieval.