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This paper presents a method of refining image search results using multiple attributes. The explosive growth of multimedia contents such as images and videos increases the difficulty of finding pieces of information from such a huge amount of contents. Users who only have a few or imprecise search conditions will be overwhelmed by the large number of search results with many of them are similar and redundant, especially when searching video frames. In this work, we utilize multiple attributes to refine search results and reduce their redundancy. We propose a technique of attribute ranking and selection in order to refine search results efficiently and effectively. In this way, we need to only use a small number of attributes that will contribute to the refinement. We demonstrate the performance of our method using real-world surveillance videos. Our proposed method can reduce up to 60% of result computation time …