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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