Título
A biometric system based on neural networks and SVM using morphological feature extraction from hand-shape images
Autor
JUAN MANUEL RAMIREZ CORTES
María del Pilar Gómez Gil
VICENTE ALARCON AQUINO
JOSE MIGUEL DAVID BAEZ LOPEZ
ROGERIO ADRIAN ENRIQUEZ CALDERA
Nivel de Acceso
Acceso Abierto
Materias
Resumen o descripción
This paper presents a hand-shape biometric system based on a novel feature extraction methodology using the morphological pattern spectrum or pecstrum. Identification experiments were carried out using the obtained feature vectors as an input to some recognition systems using neural networks and support vector machine (SVM) techniques, obtaining in average an identification of 98.5%. The verification case was analyzed through an Euclidean distance classifier, obtaining the acceptance rate (FAR) and false rejection rate (FRR) of the system for some K-fold cross validation experiments. In average, an Equal Error Rate of 2.85% was obtained. The invariance to rotation and position properties of the pecstrum allow the system to avoid a fixed hand position using pegs, as is the case in other reported systems. The results indicate that the pattern spectrum represents a good alternative of feature extraction for biometric applications.
Editor
Vilnius University
Fecha de publicación
2011
Tipo de publicación
Artículo
Versión de la publicación
Versión aceptada
Recurso de información
Formato
application/pdf
Idioma
Inglés
Audiencia
Estudiantes
Investigadores
Público en general
Sugerencia de citación
Ramirez-Cortes, J.M., et al., (2011). A biometric system based on neural networks and SVM using morphological feature extraction from hand-shape images, INFORMATICA, Vol. 22, (2): 225–240
Repositorio Orígen
Repositorio Institucional del INAOE
Descargas
1467