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nowadays, local features are widely used for content-based image retrieval. Effective feature selection is very important for the improvement of retrieval performance. Among various local feature extraction methods, Scale Invariant Feature Transform (SIFT) has been proven to be the most robust local invariant feature descriptor. However, the algorithm often generates hundreds of thousands of features...
This paper gave a visually interval algorithm for the global optimal solution to solve the problem of the constraint global optimization. This algorithm ensured that the problem cannot fall into the local optimal solution and improved the convergence speed through using local lipschitz constants. This paper proved the convergence of the algorithm, and numerical examples showed that the algorithm is...
While extracting feature vectors to represent image content remains an important issue especially those semantic features, how to measure the similarity of these feature vectors and maximize their relevance to visual content becomes an attractive research topic over the recent years. Following this trend, we proposed a new similarity measurement by introducing a correlation test into the conventional...
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