A Proposal to increase by genetic algorithm the discriminatory

Two of the most widely used techniques in the field of face recognition with infrared images are PCA (Main Component Analyzes) and LDA (Linear Discriminant Analysis). This paper presents the results obtained by using genetic algorithms to increase the discriminant power of the vectors that make up the space of characteristics generated by these techniques, by means of the weighted allocation of weights to each vector according to their level of contribution in the stage of classification. It is shown that under the proposed scheme, a lower classification error is obtained with respect to the conventional method.

• Autores: Martínez, Dúber; Loaiza C, Humberto; Caicedo B, Eduardo
• Fecha de publicación: 2011
• Institución: Universidad EAFIT
• Repositorio: Repositorio EAFIT
• Idioma: spa
• OAI Identifier: oai:repository.eafit.edu.co:10784/14473
• Acceso en línea: http://hdl.handle.net/10784/14473
• Palabra clave: Face Recognition; Infrared Images; Genetic Algorithms; Principal Component Analysis; Linear Discriminant Analysis; Reconocimiento De Rostros; Imágenes Infrarrojas; Algoritmos Genéticos; Análisis De Componentes Principales; Análisis Discriminante Lineal
• License: Copyright (c) 2011 Dúber Martínez, Humberto Loaiza C, Eduardo Caicedo B