M. A. Alimi, “A Neuro-Fuzzy Approach to Recognize Arabic Handwritten Characters,” International Conference on Neural Networks, Houston, 9-12 June 1997, pp. 1397-1400.

has been cited by the following article:

• TITLE: Genetic Algorithms for Perceptual Codes Extraction

  AUTHORS: Mahmoud Ltaief, Sourour Njah, Hala Bezine, Adel M. Alimi

  KEYWORDS: Online Handwriting; Beta-Elliptic Model; Elementary Perceptual Codes; Global Perceptual Codes; Genetic Algorithms

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.4 No.4, November 28, 2012

  ABSTRACT: In this work a new technique for global perceptual codes (GPCs) extraction using genetic algorithms (GA) is presented. GAs are employed to extract the GPCs in order to reduce the original number of features and to provide meaningful representations of the original data. In this technique the GPCs are build from a certain combination of elementary perceptual codes (EPCs) which are provided by the Beta-elliptic model for the generation of complex handwriting movements. Indeed, in this model each script is modelled by a set of elliptic arcs. We associate to each arc an EPC. In the proposed technique we defined four types of EPCs. The GPCs can be formed by many possible combinations of EPCs depending on their number and types. So that, the problem of choosing the right combination for each GPC can be regarded as a global optimization problem which is treated in this work using the GAs. Several simulation examples are presented to evaluate the interest and the efficiency of the proposed technique.