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http://hdl.handle.net/10553/44071
Título: | Discriminative common vector for face identification | Autores/as: | Travieso, Carlos M. Botella, Patricia Alonso, Jesús B. Ferrer, Miguel A. |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Biometric identification , facial recognition , classification system , Discriminative Common Vector (DVC) and Support Vector Machines (SVM). | Fecha de publicación: | 2009 | Editor/a: | 1071-6572 | Publicación seriada: | Proceedings - International Carnahan Conference on Security Technology | Conferencia: | 43rd Annual 2009 International Carnahan Conference on Security Technology, ICCST 2009 | Resumen: | 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 | Fuente: | Proceedings - International Carnahan Conference on Security Technology[ISSN 1071-6572] (5335551), p. 134-138 |
Colección: | Actas de congresos |
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