Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/28480
Type: | Conference paper |
Title: | Application of support vector machines in a texture segmentation system based on wavelet features |
Author: | Ng, B. |
Citation: | Proceedings of the 6th International Conference on Optimization: Techniques and Applications, 9-11 December 2004, Ballarat, Australia. |
Publisher: | University of Ballarat |
Publisher Place: | CD-ROM |
Issue Date: | 2004 |
ISBN: | 1876851155 |
Conference Name: | International Conference on Optimization: Techniques and Applications (6th : 2004 : Ballarat, Australia) |
Editor: | Rubinov, A. Sniedovich, M. |
Abstract: | This 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. |
Keywords: | Support Vector Machines Wavelet Transform Feature Extraction Texture Segmentation |
Description (link): | http://www.ballarat.edu.au/ard/itms/CIAO/ORBNewsletter/ICOTA/Icota_Proceedings/ |
Appears in Collections: | Aurora harvest 2 Electrical and Electronic Engineering publications |
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