Un algoritmo genético paralelo para configurar métodos de detección de defectos (A Parallel Genetic Algorithm for Configuring Defect Detection Methods)

Francisco Javier de la Calle (UO224689@uniovi.es)1, Francisco G. Bulnes (bulnes@uniovi.es)1, Daniel Fernando Garcia (dfgarcia@uniovi.es)1, Ruben Usamentiaga (rusamentiaga@uniovi.es)1, Julio Molleda (jmolleda@uniovi.es)1

1Universidad de Oviedo

This paper appears in: Revista IEEE América Latina

Publication Date: May 2015
Volume: 13,   Issue: 5 
ISSN: 1548-0992

The detection of defects in steel strips is a very important task which can improve the performance of factories by giving the possibility of early and real-time detection of defects. Defect detection methods have such a large amount of parameters that makes finding the best configuration a complex task. The search space of the value of these parameters is pretty large also, so it is necessary to use a search algorithm in order to reduce the computing time. In this article a genetic algorithm is developed for solving this search problem. The genetic algorithm looks for an optimal or sub-optimal solution without examining the whole search space. In addition, the computing time can be reduced by running the algorithm on a grid of computers. The genetic algorithm designed allows a near-optimal configuration of defect detection methods in a short time.

Index Terms:
genetic algorithn, defect detection, computer vision, non-invasive detection, parallel algorithm   

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