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
Geran Gharakhili,F. , Hakkak,M. and Mohammadi,A. (2005). Evaluation of Dissimilarity Measures for Image Retrieval and Classification. The Modares Journal of Electrical Engineering, 5(0), 1-9.
MLA
Geran Gharakhili,F. , Hakkak,M. , and Mohammadi,A. . "Evaluation of Dissimilarity Measures for Image Retrieval and Classification", The Modares Journal of Electrical Engineering, 5, 0, 2005, 1-9.
HARVARD
Geran Gharakhili,F.,Hakkak,M.,Mohammadi,A. (2005). 'Evaluation of Dissimilarity Measures for Image Retrieval and Classification', The Modares Journal of Electrical Engineering, 5(0), pp. 1-9.
CHICAGO
F. Geran Gharakhili, M. Hakkak and A. Mohammadi, "Evaluation of Dissimilarity Measures for Image Retrieval and Classification," The Modares Journal of Electrical Engineering, 5 0 (2005): 1-9,
VANCOUVER
Geran Gharakhili,F.,Hakkak,M.,Mohammadi,A. Evaluation of Dissimilarity Measures for Image Retrieval and Classification. The Modares Journal of Electrical Engineering, 2005; 5(0): 1-9.
The Modares Journal of Electrical Engineering