CBIR system with relevance feedback using Hölder exponent

Abstract

In this paper Content Base Image Retrieval (CBIR) system with relevance feedback is presented, where image database search is performed using singularity strength (Holder exponent). Images in database are described with low-level features for color and texture, which are concatenated in feature vectors (FV). Relevance feedback is implemented in CBIR system employing the artificial intelligence based on Radial Bases Functions. Feature vectors are refined using local singularities. Search efficiency of the CBIR system is compared for direct and refined feature vector. CBIR system is tested on Corel 1000 image database. The test results showed that CBIR system using local singularities has high search efficiency, and the search results are comparable with the results for direct feature vectors.