Region-based image retrieval using relevance feature weights

Abstract

We propose a new region-based CBIR (content-based image retrieval) system. One of the main objectives of our work is to reduce the semantic gap between the visual characteristics of the query and the high level semantic sought by the user. This is achieved by allowing the user to select specific regions and expressing his interest in a more accurate way. Moreover, the proposed approach overcomes the challenge of choosing suitable features to describe the image content. More specifically, relevance weights are automatically associated with each visual feature in order to better represent the visual content of the images. To evaluate these objectives, we compare the obtained results with those obtained using traditional CBIR systems.