Exploiting clustering approaches for image re-ranking
Journal of Visual Languages and Computing
Using contextual spaces for image re-ranking and rank aggregation
Multimedia Tools and Applications
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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.