In this present work, we are proposing a
characteristics reduction system for a facial biometric
identification system, using transformed domains such as
discrete cosine transformed (DCT) and discrete wavelets
transformed (DWT) as parameterization; and Support Vector
Machines (SVM) and Neural Network (NN) as classifiers. ...»»»»
In this present work, we are proposing a
characteristics reduction system for a facial biometric
identification system, using transformed domains such as
discrete cosine transformed (DCT) and discrete wavelets
transformed (DWT) as parameterization; and Support Vector
Machines (SVM) and Neural Network (NN) as classifiers. The
size reduction has been done with Principal Component
Analysis (PCA) and with Independent Component Analysis
(ICA). This system presents a similar success results for both
DWT-SVM system and DWT-PCA-SVM system, about 98%.
The computational load is improved on training mode due to
the decreasing of input’s size and less complexity of the
classifier.^^^^
Tipus:
Conferència
Citació Bibliogràfica:
C.M. Travieso, J. Solé-Casals, V. Zaiats, J.B. Alonso, M.A. Ferrer, “Reducción del vector de características en reconocimiento facial», XXII Simposium de la Unión Científica Internacional de Radio URSI'2008 Universidad Complutense de Madrid, Madrid, setembre de 2008