A recursive optimal relevance feedback scheme for content based image retrieval

In this paper, an optimal relevance algorithm is proposed, which adapts the response of a content-based image retrieval (CBIR) system to the user's information needs. In particular, the importance of each descriptor to the similarity measure of the system is estimated so that the correlation between the query image and all images marked by the user as relevant is maximized while simultaneously the correlation over all irrelevant images is minimized. Other degree of relevance can be also included in the proposed scheme. In case that the user applies more than one feedback iterations, a recursive algorithm is introduced for increasing the system efficiency. Convergence of the proposed scheme is achieved if "consistent" relevant and irrelevant images are selected by the user.

• Type: Conference
• Year: 2001
• Where: ICIP
• Authors: Anastasios D. Doulamis, Nikolaos D. Doulamis
• Keywords: Content-based Image Retrieval, ICIP 2001, Image Processing, Irrelevant Images, Optimal Relevance Algorithm