Image Retrieval Using Multi-granularity Features of Color and Texture

Making full use of image information with its own to extract features is the crucial problem in content based image retrieval (CBIR). In this paper, quotient space(QS) granularity computing theory is imported into image retrieval field, granularity thinking in image retrieval is clarified, and a novel image retrieval method is proposed. Firstly, aiming at the different behaviors under different granularities, color and texture features are obtained respectively under different granularities, different quotient spaces are achieve; secondly, do the attribute combination to the obtained quotient spaces according to the quotient space granularity combination principle; and then realize image retrieval using the combined attribute function. Comparing with methods adopting single attribute feature the image retrieval method based on quotient space granularity combination utilizes the image information with its own in a more effective way. The experimental results demonstrate the feasibility and validity of the proposed method.