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.
Nezamabadi-Pour,H. and Kabir,E. (2005). » Research Note « Evaluation of Dissimilarity Measures for Image Retrieval and Classification. The Modares Journal of Electrical Engineering, 5(0), 89-98.
MLA
Nezamabadi-Pour,H. , and Kabir,E. . "» Research Note « Evaluation of Dissimilarity Measures for Image Retrieval and Classification", The Modares Journal of Electrical Engineering, 5, 0, 2005, 89-98.
HARVARD
Nezamabadi-Pour,H.,Kabir,E. (2005). '» Research Note « Evaluation of Dissimilarity Measures for Image Retrieval and Classification', The Modares Journal of Electrical Engineering, 5(0), pp. 89-98.
CHICAGO
H. Nezamabadi-Pour and E. Kabir, "» Research Note « Evaluation of Dissimilarity Measures for Image Retrieval and Classification," The Modares Journal of Electrical Engineering, 5 0 (2005): 89-98,
VANCOUVER
Nezamabadi-Pour,H.,Kabir,E. » Research Note « Evaluation of Dissimilarity Measures for Image Retrieval and Classification. The Modares Journal of Electrical Engineering, 2005; 5(0): 89-98.
The Modares Journal of Electrical Engineering