Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44071
Title: Discriminative common vector for face identification
Authors: Travieso, Carlos M. 
Botella, Patricia
Alonso, Jesús B. 
Ferrer, Miguel A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Biometric identification , facial recognition , classification system , Discriminative Common Vector (DVC) and Support Vector Machines (SVM).
Issue Date: 2009
Publisher: 1071-6572
Journal: Proceedings - International Carnahan Conference on Security Technology 
Conference: 43rd Annual 2009 International Carnahan Conference on Security Technology, ICCST 2009 
Abstract: In this paper, it is proposed a facial biometric identification system, using discriminative common vector. This method reduces the number of characteristics of the different images from the database and selects the most discriminative of them. In this work, transformed domains, such as discrete cosine transformed (DCT), discrete wavelets transformed (DWT), principal component analysis (PCA), linear discriminative analysis (LDA) and independent component analysis (ICA) are also used. As classifier systems a support vector machines (SVM) and a neuronal network (NN) have been utilized. With the above system, a simple and robust system with good results has been obtained. Using DCV, our experiments have reached a success rate of 99.13%plusmn0.23 for ORL and 99.4%plusmn0.35 for Yale.
URI: http://hdl.handle.net/10553/44071
ISBN: 9781424441709
ISSN: 1071-6572
DOI: 10.1109/CCST.2009.5335551
Source: Proceedings - International Carnahan Conference on Security Technology[ISSN 1071-6572] (5335551), p. 134-138
Appears in Collections:Actas de congresos
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