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Proceedings Paper

Cascade-system genetic algorithm: multilayer neural network for a supervised classification of texture images
Author(s): M. Nasri; R. Aboutni; M. EL Hitmy; H. Nait Charif; M. Barboucha
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Paper Abstract

Classifying texture images is the operation of differentiating between them in the parameters space. Selecting the pertinent parameters for the classification is a very delicate procedure. We present in this paper a new approach of texture image classification based on a cascade system, genetic algorithm - multi-layer neural network. We start by using a genetic approach to optimize the choice of parameters by minimizing a cost function. Then, later on, we realize a supervised classifier based on a multi-layer neural network. The pertinent parameters obtained by the genetic algorithm are used as the inputs of the neural network. This approach is validated on some texture images. The proposed algorithm converges rapidly to the optimal solution with a low rate of misclassification.

Paper Details

Date Published: 1 May 2003
PDF: 9 pages
Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); doi: 10.1117/12.514957
Show Author Affiliations
M. Nasri, Univ. of Oujda (Morocco)
R. Aboutni, Univ. of Oujda (Morocco)
M. EL Hitmy, Univ. of Oujda (Morocco)
H. Nait Charif, Univ. of Oujda (Morocco)
M. Barboucha, Univ. of Oujda (Morocco)

Published in SPIE Proceedings Vol. 5132:
Sixth International Conference on Quality Control by Artificial Vision
Kenneth W. Tobin Jr.; Fabrice Meriaudeau, Editor(s)

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