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Communication Dans Un Congrès Année : 2013

K-centroids based supervised classification of texture images: handling the intra-class diversity

Résumé

Natural texture images exhibit a high intra-class diversity due to different acquisition conditions (scene enlightenment, perspective angle, . . . ). To handle with the diversity, a new supervised classification algorithm based on a parametric formalism is introduced: the K-centroids-based classifier (K-CB). A comparative study between various supervised classification algorithms on the VisTex and Brodatz image databases is conducted and reveals that the proposed K-CB classifier obtains relatively good classification accuracy with a low computational complexity.
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Dates et versions

hal-00841939 , version 1 (05-07-2013)

Identifiants

  • HAL Id : hal-00841939 , version 1

Citer

Aurélien Schutz, Lionel Bombrun, Yannick Berthoumieu. K-centroids based supervised classification of texture images: handling the intra-class diversity. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013, Vancouver, Canada. pp.1498-1502. ⟨hal-00841939⟩
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