Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44063
Title: Robust identification of persons by lips contour using shape transformation
Authors: Briceño, Juan C.
Travieso, Carlos M. 
Alonso, Jesús B. 
Ferrer, Miguel A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Robustness , Identification of persons , Lips , Shape , Hidden Markov models , Support vector machines , Face detection , Kernel , Support vector machine classification , Biometrics
Issue Date: 2010
Journal: INES 2010 - 14th International Conference on Intelligent Engineering Systems, Proceedings
Conference: 14th International Conference on Intelligent Engineering Systems, INES 2010 
Abstract: In this paper we present a biometric approach, based on lip shape. We have performed an image preprocessing, in order to detect the face of a person image. After this, we have enhanced the lips image using a color transformation, and next we do its detection. The parameterization is based on lips contour points. Those points have been transformed by a Hidden Markov Model (HMM) kernel, using a minimization of Fisher Score. Finally, a one-versus-all multiclass supervised approach based on Support Vector Machines (SVM) is applied as a classifier. A database with 50 users and 10 samples per class has been built. A cross-validation strategy have been applied in our experiments, reaching success rates up to 99.6%, using four lip training samples per class, and evaluating with six lip test samples. This success was found using a shape of 150 points, with 40 states in Hidden Markov Model and a RBF kernel for a supervised approach based on Support Vector Machines.
URI: http://hdl.handle.net/10553/44063
ISBN: 9781424476527
DOI: 10.1109/INES.2010.5483848
Source: INES 2010 - 14th International Conference on Intelligent Engineering Systems, Proceedings (5483848), p. 203-207
Appears in Collections:Actas de congresos
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