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Supervised texture segmentation using DWT and a modified K-NN classifier

Conference Paper


Abstract


  • Texture segmentation has been an important problem in image processing. Filtering approaches have been popular, and recent studies have indicated a need for efficient, low-complexity algorithms. In this paper, we present a texture segmentation scheme based on the Discrete Wavelet Transform (DWT). The DWT is a non-redundant representation which can reduce computational complexity in the processing. The texture segmentation scheme presented here consists of three steps: feature extraction, conditioning, and clustering. For feature conditioning, a number of smoothing windows have been tested. Clustering is performed with a modified K-NN clustering algorithm. The proposed scheme consistently achieves error rates of less than 10% with the best average error of 5.62%. © 2000 IEEE.

Publication Date


  • 2000

Citation


  • Ng, B. W., & Bouzerdoum, A. (2000). Supervised texture segmentation using DWT and a modified K-NN classifier. In Proceedings - International Conference on Pattern Recognition Vol. 15 (pp. 545-548).

Scopus Eid


  • 2-s2.0-34147096628

Start Page


  • 545

End Page


  • 548

Volume


  • 15

Issue


  • 2

Abstract


  • Texture segmentation has been an important problem in image processing. Filtering approaches have been popular, and recent studies have indicated a need for efficient, low-complexity algorithms. In this paper, we present a texture segmentation scheme based on the Discrete Wavelet Transform (DWT). The DWT is a non-redundant representation which can reduce computational complexity in the processing. The texture segmentation scheme presented here consists of three steps: feature extraction, conditioning, and clustering. For feature conditioning, a number of smoothing windows have been tested. Clustering is performed with a modified K-NN clustering algorithm. The proposed scheme consistently achieves error rates of less than 10% with the best average error of 5.62%. © 2000 IEEE.

Publication Date


  • 2000

Citation


  • Ng, B. W., & Bouzerdoum, A. (2000). Supervised texture segmentation using DWT and a modified K-NN classifier. In Proceedings - International Conference on Pattern Recognition Vol. 15 (pp. 545-548).

Scopus Eid


  • 2-s2.0-34147096628

Start Page


  • 545

End Page


  • 548

Volume


  • 15

Issue


  • 2