Abstract—Relevance feedback and region based image retrieval are two effective ways to improve accuracy in content-based image retrieval. In this paper, we propose a content-based image retrieval method using relevance feedback and homogeneous region. By extracting a number of homogeneous color regions from the image and calculating the occurrence frequency of regions, we convert image feature vectors to weighted vectors. On the basis of the weighted vectors, we calculate the similarity between two weighted vectors and using relevant feedback technique. Our experimental results on a Wang database of over 10,000 images suggest that the technique results in which is close to user’s intention better than the CBsIR and CCH methods. 

Index Terms—content based image retrieval, weighted vectors, feature vectors, machine learning

Cite: Vu Van Hieu and Nguyen Huu Quynh, "An Image Retrieval Method Using Homogeneous Region and Relevance Feedback," International Journal of Signal Processing Systems, Vol. 3, No. 1, pp. 14-18, June 2015. doi: 10.12720/ijsps.3.1.14-18