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Authors: Ahmed Kharrat 1 ; Nacéra Benamrane 1 ; Mohamed Ben Messaoud 2 and Mohamed Abid 2

Affiliations: 1 University of Sfax, Faculty of Science and Vision and Medical Imagery Laboratory U.S.T.O., Tunisia ; 2 University of Sfax, Tunisia

ISBN: 978-989-8425-47-8

Keyword(s): Support vector machine, Classification, Genetic algorithm, Parameters optimisation, Feature selection.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Early Vision and Image Representation ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Segmentation and Grouping ; Signal Processing, Sensors, Systems Modeling and Control ; Statistical Approach ; Wavelet Analysis

Abstract: The parameter selection is very important for successful modelling of input–output relationship in a function classification model. In this study, support vector machine (SVM) has been used as a function classification tool for accurate segregation and genetic algorithm (GA) has been utilised for optimisation of the parameters of the SVM model. Having as input only five selected features, parameters optimisation for SVM is applied. The five selected features are mean of contrast, mean of homogeneity, mean of sum average, mean of sum variance and range of autocorrelation. The performance of the proposed model has been compared with a statistical approach. Despite the fact that Grid algorithm has fewer processing time, it does not seem to be efficient. Testing results show that the proposed GA–SVM model outperforms the statistical approach in terms of accuracy and computational efficiency.

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Paper citation in several formats:
Kharrat, A.; Benamrane, N.; Ben Messaoud, M. and Abid, M. (2011). EVOLUTIONARY SUPPORT VECTOR MACHINE FOR PARAMETERS OPTIMIZATION APPLIED TO MEDICAL DIAGNOSTIC.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 201-204. DOI: 10.5220/0003326902010204

@conference{visapp11,
author={Ahmed Kharrat. and Nacéra Benamrane. and Mohamed Ben Messaoud. and Mohamed Abid.},
title={EVOLUTIONARY SUPPORT VECTOR MACHINE FOR PARAMETERS OPTIMIZATION APPLIED TO MEDICAL DIAGNOSTIC},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={201-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003326902010204},
isbn={978-989-8425-47-8},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - EVOLUTIONARY SUPPORT VECTOR MACHINE FOR PARAMETERS OPTIMIZATION APPLIED TO MEDICAL DIAGNOSTIC
SN - 978-989-8425-47-8
AU - Kharrat, A.
AU - Benamrane, N.
AU - Ben Messaoud, M.
AU - Abid, M.
PY - 2011
SP - 201
EP - 204
DO - 10.5220/0003326902010204

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