Content-based image retrieval algorithm oriented by users´ experience

In order to not only improve the storage efficiency, retrieval speed and accuracy of the existing content-based image retrieval algorithm, but also improve the quality of user experience, this paper proposes a novel improved algorithm about content-based image retrieval oriented by users´ experience. According to the three elements of human visual color characteristics, this algorithm firstly quantifies the image; then it calculates the histogram in HSV color space. With the feature vectors of the obtained histogram, the index will be set in Lucene indexing library. At the same time, users´ relevance feedback information is made use of to modify the searching results, which makes results closer to users´ needs. Experimental results show that the proposed algorithm has perfect efficiency and accuracy, which makes users´ operating experience better.