Cascade-system genetic algorithm: multilayer neural network for a supervised classification of texture images

M. Nasri; R. Aboutni; M. EL Hitmy; H. Nait Charif; M. Barboucha

doi:10.1117/12.514957

1 May 2003 Cascade-system genetic algorithm: multilayer neural network for a supervised classification of texture images

M. Nasri, R. Aboutni, M. EL Hitmy, H. Nait Charif, M. Barboucha

Author Affiliations +

Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.514957
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States

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.

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M. Nasri, R. Aboutni, M. EL Hitmy, H. Nait Charif, and M. Barboucha "Cascade-system genetic algorithm: multilayer neural network for a supervised classification of texture images", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.514957

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