A Survey of Content-Based Image Retrieval Systems using Scale-Invariant Feature Transform (SIFT)

Content-based image retrieval (CBIR) is a method for finding similar images from large image databases. As the network and development of multimedia technologies are becoming more popular, users are not satisfied with the traditional information retrieval techniques. In recent years, local descriptors are used as image features to improve the performance of CBIR. The SIFT is one of the most local feature detector and descriptors used in many computer vision applications. This paper provides the surveys of CBIR systems that using SIFT algorithm to extract the local features of images.

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