An Integrated Global and Fuzzy Regional Approach to Content-Based Image Retrieval

This paper proposes an effective and efficient approach to content-based image retrieval by integrating global visual features and fuzzy region-based color and texture features. The Cauchy function is utilized to fuzzify each independent regional color and texture feature for addressing the issues associated with the color/texture inaccuracies and segmentation uncertainties. The overall similarity measure is computed as a weighted combination between global and regional similarity measures incorporating all features. Our proposed approach demonstrates a promising performance on an image database of 1000 general-purpose images from COREL, as compared with some variants of the proposed method and some peer systems in the literature.