Ng, B.Rubinov, A.Sniedovich, M.2007-05-142007-05-142004Proceedings of the 6th International Conference on Optimization: Techniques and Applications, 9-11 December 2004, Ballarat, Australia.1876851155http://hdl.handle.net/2440/28480This paper investigates the application of Support Vector Machines (SVMs) to segment images based on textural information. The textures are subjected to a wavelets-based feature extraction process with the extracted features used by the SVM for classification. Both binary and multi-class cases are considered, with the latter using a one-against-one approach. Experimental results show an improvement over SVM classification using direct grayscale values as input vectors, while being more robust than alternative classifiers with the same texture features.enSupport Vector MachinesWavelet TransformFeature ExtractionTexture SegmentationConference paper002004128556404Ng, B. [0000-0002-8316-4996]