AN EFFECTIVE METHOD OF IMAHE RETRIEVAL BASED ON MODIFIED FUZZY C-MEANS CLUSTERING SCHEME

With the development of multimedia network technology and the rapid increase of image application, content-based image retrieval (CBIR) becomes the most active one in multimedia information retrieval field. One of the key issues in CBIR is how to construct effective organization and index to enhance image retrieval speed. Clustering is a kind of effective method. This paper presents a modified fuzzy C-means (MFCM) clustering index scheme method. In addition, in order to reduce the time of clustering, high-dimension feature space is transformed into lower-dimension space by using Karhunen-Loeve (K-L) transformation. The clustering step is performed in lower-dimension space, and image retrieval is only performed in clustered prototypes. Experimental results show that MFCM applied to image retrieval is effectively, exact and real-time. The time of retrieval doesn´t increase linearly with the extended image database. It is superior to traditional C-means and fuzzy C-means clustering algorithms