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 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 algorithm. 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 index algorithm applied to image retrieval is effective, exact and real-time. The time of retrieval doesn't increase linearly with the extended image database.
An Effective and Fast Retrieval Algorithm for Content-Based Image Retrieval
2008 Congress on Image and Signal Processing ; 2 ; 471-474
01.05.2008
680754 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Here's Waldo: Content Based Image Retrieval
British Library Online Contents | 1998
|A content-based image retrieval system
British Library Online Contents | 1998
|Fast progressively refined image retrieval
British Library Online Contents | 1998
|Learning semantics in content based image retrieval
IEEE | 2003
|Texture Classification for Content-Based Image Retrieval
British Library Conference Proceedings | 2001
|