A fast and efficient image retrieval system based on color and texture features

We propose a fast and efficient image retrieval system based on color and texture features. The color features are represented by color histograms and texture features are represented by block difference of inverse probabilities (BDIP) and block variation of local correlation coefficients (BVLC). It is observed that color features in combination with the texture features derived on the brightness component provides approximately similar results when color features are combined with the texture features using all three components of color, but with much less processing time. An analysis of various distance measures reveals that the square-chord distance measure outperforms the other prominent distance measures for the proposed method. Detailed experimental analysis is carried out using precision and recall on four datasets: Corel-5K, Corel-10K, UKbench and Holidays. The time analysis is also performed to compare processing speeds of the proposed method with the existing similar best methods.