Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44088
Title: Multifeature knuckles parameterization
Authors: Morales, Aythami
Henriquez, P. 
Alonso Hernández, Jesús Bernardino 
Travieso González, Carlos Manuel 
Ferrer Ballester, Miguel Ángel 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Biometrics, Knuckles8Gabor filter, Image processing, SVM
Issue Date: 2008
Journal: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008
Conference: IASTED International Conference on Artificial Intelligence and Applications, AIA 2008 
Abstract: 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
Source: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008, p. 205-209
Appears in Collections:Actas de congresos
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