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Information Journal Paper

Title

EVALUATION OF DISSIMILARITY MEASURES FOR IMAGE RETRIEVAL AND CLASSIFICATION (RESEARCH NOTE)

Pages

  89-98

Abstract

 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.      

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    APA: Copy

    NEZAMABADI POUR, H., & KABIR, E.. (2006). EVALUATION OF DISSIMILARITY MEASURES FOR IMAGE RETRIEVAL AND CLASSIFICATION (RESEARCH NOTE). MODARES TECHNICAL AND ENGINEERING, -(22), 89-98. SID. https://sid.ir/paper/25103/en

    Vancouver: Copy

    NEZAMABADI POUR H., KABIR E.. EVALUATION OF DISSIMILARITY MEASURES FOR IMAGE RETRIEVAL AND CLASSIFICATION (RESEARCH NOTE). MODARES TECHNICAL AND ENGINEERING[Internet]. 2006;-(22):89-98. Available from: https://sid.ir/paper/25103/en

    IEEE: Copy

    H. NEZAMABADI POUR, and E. KABIR, “EVALUATION OF DISSIMILARITY MEASURES FOR IMAGE RETRIEVAL AND CLASSIFICATION (RESEARCH NOTE),” MODARES TECHNICAL AND ENGINEERING, vol. -, no. 22, pp. 89–98, 2006, [Online]. Available: https://sid.ir/paper/25103/en

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