In this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. The precision-recall measure and the correct classification rate of the k-NN classifier are used to evaluate retrieval and classification performances, respectively. The experimental results for a database of 1000 images from 10 different semantic groups, based on color histogram, directional edge histogram and Gabor features are presented and discussed.

Keywords: Dissimilarity measure, Low-level feature, Semantic feature, Classification, : Content-based image retrieval

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