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Distances Correlation for Re-ranking in Content-Based Image Retrieval
2010
2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images
Content-based image retrieval relies on the use of efficient and effective image descriptors. One of the most important components of an image descriptor is concerned with the distance function used to measure how similar two images are. This paper presents a clustering approach based on distances correlation for computing the similarity among images. Conducted experiments involving shape, color, and texture descriptors demonstrate the effectiveness of our method.
doi:10.1109/sibgrapi.2010.9
dblp:conf/sibgrapi/PedronetteT10
fatcat:y64xebrnjrecvkjdwgzdvjcgr4