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. & 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., & 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
Geran Gharakhili, F., Hakkak, M. & Mohammadi, A., "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