International Journal of Engineering and Technology

An efficient search for semantically relevant images has always been thirst in computer vision and processing specially in large scale image retrieval. We propose an integrated approach for fast and effective image retrieval system using multiple features and hsv histogram. Relevance feedback allows user interaction to improve the performance. Features used in this work are improved lbp and modified fourier descriptors, plays vital role in effective retrieval. Experimental results on CALTECH-101 and MPEG CE shape 1 datasets proves that our framework provides better retrieval efficiency compared to the state of art methods.