Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/44088
Título: Multifeature knuckles parameterization
Autores/as: Morales, Aythami
Henriquez, P. 
Alonso Hernández, Jesús Bernardino 
Travieso González, Carlos Manuel 
Ferrer Ballester, Miguel Ángel 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Biometrics, Knuckles8Gabor filter, Image processing, SVM
Fecha de publicación: 2008
Publicación seriada: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008
Conferencia: IASTED International Conference on Artificial Intelligence and Applications, AIA 2008 
Resumen: A biometric verification system based on the hand knuckles texture is presented in this paper. The system selects the knuckles area of the hand image and work out three different versions of the image called: gray scale, enhance black and white, and Gabor filtered. The first 15 by 15 DCT coefficients of each knuckle image version are obtained and save as three different feature sets. In order to verify the claimed identity, a support vector machine for feature set is used and the three schemes are combined at score level. The system has been tested with a multisession database which contains 42 individuals. Training with the first session images and testing with the second and third session images the system reaches an EER equal to 2,86%.
URI: http://hdl.handle.net/10553/44088
ISBN: 9780889867093
Fuente: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008, p. 205-209
Colección:Actas de congresos
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