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Empirical evaluation of dissimilarity measures for color and texture

Publication ,  Journal Article
Puzicha, J; Buhmann, JM; Rubner, Y; Tomasi, C
Published in: Proceedings of the IEEE International Conference on Computer Vision
January 1, 1999

This paper empirically compares nine image dissimilarity measures that are based on distributions of color and texture features summarizing over 1,000 CPU hours of computational experiments. Ground truth is collected via a novel random sampling scheme for color, and via an image partitioning method for texture. Quantitative performance evaluations are given for classification, image retrieval, and segmentation tasks, and for a wide variety of dissimilarity measures. It is demonstrated how the selection of a measure, based on large scale evaluation, substantially improves the quality of classification, retrieval, and unsupervised segmentation of color and texture images.

Duke Scholars

Published In

Proceedings of the IEEE International Conference on Computer Vision

ISSN

1550-5499

Publication Date

January 1, 1999

Volume

2

Start / End Page

1165 / 1172
 

Citation

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MLA
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Puzicha, J., Buhmann, J. M., Rubner, Y., & Tomasi, C. (1999). Empirical evaluation of dissimilarity measures for color and texture. Proceedings of the IEEE International Conference on Computer Vision, 2, 1165–1172.
Puzicha, J., J. M. Buhmann, Y. Rubner, and C. Tomasi. “Empirical evaluation of dissimilarity measures for color and texture.” Proceedings of the IEEE International Conference on Computer Vision 2 (January 1, 1999): 1165–72.
Puzicha J, Buhmann JM, Rubner Y, Tomasi C. Empirical evaluation of dissimilarity measures for color and texture. Proceedings of the IEEE International Conference on Computer Vision. 1999 Jan 1;2:1165–72.
Puzicha, J., et al. “Empirical evaluation of dissimilarity measures for color and texture.” Proceedings of the IEEE International Conference on Computer Vision, vol. 2, Jan. 1999, pp. 1165–72.
Puzicha J, Buhmann JM, Rubner Y, Tomasi C. Empirical evaluation of dissimilarity measures for color and texture. Proceedings of the IEEE International Conference on Computer Vision. 1999 Jan 1;2:1165–1172.

Published In

Proceedings of the IEEE International Conference on Computer Vision

ISSN

1550-5499

Publication Date

January 1, 1999

Volume

2

Start / End Page

1165 / 1172