%0 Journal Article
%A GENG Guo-hua
%A SUN Ting
%T CBIR Algorithm Based on Relevance Feedback and Robust Local Binary Patterns
%D 2016
%R 10.13190/j.jbupt.2016.05.004
%J Journal of Beijing University of Posts and Telecommunications
%P 16-19
%V 39
%N 5
%X A algorithm of content based image retrieval (CBIR) based on robust local binary patterns (RLBP) and relevance feedback (RF) was proposed. RLBP is a kind of feature extraction operator with good performance, which has strong robustness to the noise and illumination changes. The original data will not be changed with RLBP, and the accuracy of feature extraction can be improved. RF enables the system to learn the user's preferences and guide the search results. Experiments with several texture databases show that the accuracy and robustness of the proposed algorithm is better than that of the similar algorithms.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2016.05.004