Interactive Image Retrieval in a Fuzzy Framework

In this paper, an interactive image retrieval scheme using MPEG-7 visual descriptors is proposed. The performance of image retrieval systems is still limited due to semantic gap, which is created from the discrepancies between the computed low-level features (color, texture, shape, etc.) and user's conception of an image. As a result, more interest has been created towards development of efficient learning mechanism other than designing sophisticated low-level feature extraction algorithms. A simple relevance feedback mechanism is proposed, that learns user's interest and updates feature weights based on a fuzzy feature evaluation measure. This has an advantage of handling comparatively small number of samples over those using standard classifiers involving large number of training samples and having more complexity. Extensive experiments have been performed to test to what extent the performance of an image retrieval system can be enhanced further using MPEG-7 standard visual features at minimum cost.