A new system for image retrieval using beta wavelet network for descriptors extraction and fuzzy decision support
Asma El Adel, Ridha Ejbali, Mourad Zaied, Chokri Ben Amar · 2014
Image retrieval has been popular for several years. There are different system designs for content-based image retrieval (CBIR). So, it is very important to find effective and efficient feature extraction techniques. This paper proposes a new local approach for CBIR system which combines mechanisms including content-based image, as well as fuzzy systems. First, we exploit Beta Wavelet Network Analysis (BWNA) to extract three descriptors which are shape, texture and color. Then, we propose a fuzzy decision support system, with three inputs, for descriptors fusion and better making final decision. The experimental results show the robustness and the efficiency of the proposed system for CBIR.