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With the rapid development of the Internet, finding desired images from numerous images has become an important research topic. In this paper, we propose an image retrieval system facilitating retrieval time and accuracy. Since the performance of image retrieval is deeply influenced by image features and retrieval methods. Five different types of features and five different methods are used to find the best combination for an image retrieval system. First, we segment out the main object in an image and then extract its features. Next, relevant features are selected from the original feature set for facilitating image retrieval, using the SAHS algorithm. Then, five methods based on AND/OR-construction are proposed to build the image retrieval model, using the relevant features. Finally, the experimental results not only show that our methods are more effective than the other state-of-the-art methods but also present some observations never explored by the previous research.
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