Texture classification using finite Ridgelet transform and support vector machines

Authors:
Yunxia Liu;Yuhua Peng;Xinhong Zhou
Affiliations:
School of Information Science and Engineering, Shandong University, Jinan, Shandong, China;School of Information Science and Engineering, Shandong University, Jinan, Shandong, China;School of Information Science and Engineering, Shandong University, Jinan, Shandong, China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

Citing 6
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Abstract

Based on energy distribution analysis of FRIT coefficients, a novel feature extraction method of low computation complexity in FRIT domain was proposed for texture classification in this paper. A 'one-against-one' multi-class SVM with RBF kernel was adopted as classifier. Experiments carried out on abundant texture databases with varying sizes demonstrated its validity.