Content Based Image Retrieval System using Clustering with Combined Patterns

This paper presents content-based image retrieval (CBIR) system for the multi object images and also a novel framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency. Color, texture and shape information have been the primitive image descriptors in content based image retrieval systems. The goal is to retrieve those images from the database, which contains the query object, which is a difficult problem when an image consists of multiple objects with arbitrary pose. The color moments and moments on Gabor filter responses of these tiles serve as local descriptors of color and texture respectively. The combination of the color, texture and shape features provide a robust feature set for image retrieval. The experimental results demonstrate the efficiency of the method. The proposed approach is simple and easy to adopt. The proposed system shows good results in terms of improvement in retrieval quality, in comparison with the literature.