Published
Using genetic algorithm feature selection in neural classification systems for image pattern recognition
Implementación de selección de características con algoritmos genéticos en clasificadores neuronales para reconocimiento de patrones en imágenes
Keywords:
Feature vector, genetic algorithm, neural network, pattern recognition. (en)Algoritmos Genéticos, Vector De Características, Redes Neuronales, Reconocimiento de Patrones. (es)
Pattern recognition performance depends on variations during extraction, selection and classification stages. This paper presents an approach to feature selection by using genetic algorithms with regard to digital image recognition and quality control. Error rate and kappa coefficient were used for evaluating the genetic algorithm approach Neural networks were used for classification, involving the features selected by the genetic algorithms. The neural network approach was compared to a K-nearest neighbour classifier. The proposed approach performed better than the other methods.
El desempeño en el reconocimiento de patrones depende de las variaciones en las etapas de extracción, selección y clasificación. En el siguiente artículo se presenta un enfoque para selección de características utilizando un algoritmo genético aplicado a procesos de reconocimiento y control de calidad en imágenes. Para evaluar la propuesta con algoritmos genéticos se utilizan dos funciones de evaluación: tasa de error y coeficiente Kappa. Se implementan redes neuronales en la clasificación usando las características seleccionadas por el algoritmo genético. La red neuronal se compara con el clasificador de los k-vecinos. Los resultados obtenidos muestran un mejor desempeño del sistema propuesto frente a otros métodos.
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