TY - GEN
T1 - Hybrid methodology focused on the model of binary patterns and the theory of fuzzy logic for facial biometric verification and identification
AU - Nava, Sergio González
AU - Silva, Alberto J.Rosales
AU - Montiel, Nidiyare Hevia
AU - Funes, Francisco J.Gallegos
AU - González, Mario Dehesa
N1 - Publisher Copyright:
© Copyright 2015 by SCITEPRESS - Science and Technology Publications, Lda.
PY - 2015
Y1 - 2015
N2 - It is proposed a methodology to improve verification and identification biometric facial indicators based in hybridization binary pattern models and the fuzzy logic theory, making besides use of the traditional image pre-procebing models, feature extraction and clabifiers to validate the performance of the proposal methodology. The facial recognition is complicated due to the variability of the facial appearance related the same person, and the small characteristic samples for each person in adverse conditions. To fix this, is considered the binary pattern models as an excellent choice to the local face representations, whose more important properties is their tolerance against the variations of luminance, scale and rotation. However, the binary pattern model is sensitive to small variations of the pixel intensities, generally caused by the noise, which introduce uncertainty to the texture and contrast representation of the facial image. Using fuzzy logic in the binary patterns calculation, leads to a texture representation model that takes into account the uncertainty of the contained information in each image, providing a better representation of texture and contrast measure. In combination with traditional algorithms in the pre-procebing stage, as photometric and histogram normalization, the feature extraction stage is achieved using linear discriminants and Gabor wavelets to provide finally a stage of the support vector machines clabification.
AB - It is proposed a methodology to improve verification and identification biometric facial indicators based in hybridization binary pattern models and the fuzzy logic theory, making besides use of the traditional image pre-procebing models, feature extraction and clabifiers to validate the performance of the proposal methodology. The facial recognition is complicated due to the variability of the facial appearance related the same person, and the small characteristic samples for each person in adverse conditions. To fix this, is considered the binary pattern models as an excellent choice to the local face representations, whose more important properties is their tolerance against the variations of luminance, scale and rotation. However, the binary pattern model is sensitive to small variations of the pixel intensities, generally caused by the noise, which introduce uncertainty to the texture and contrast representation of the facial image. Using fuzzy logic in the binary patterns calculation, leads to a texture representation model that takes into account the uncertainty of the contained information in each image, providing a better representation of texture and contrast measure. In combination with traditional algorithms in the pre-procebing stage, as photometric and histogram normalization, the feature extraction stage is achieved using linear discriminants and Gabor wavelets to provide finally a stage of the support vector machines clabification.
KW - Binary Patterns
KW - Facial Biometrics
KW - Fuzzy Logic
KW - Image Procebing
KW - Pattern Recognition
UR - http://www.scopus.com/inward/record.url?scp=84960959653&partnerID=8YFLogxK
M3 - Contribución a la conferencia
AN - SCOPUS:84960959653
T3 - IJCCI 2015 - Proceedings of the 7th International Joint Conference on Computational Intelligence
SP - 180
EP - 187
BT - FCTA
A2 - Dourado, Antonio
A2 - Ruano, Antonio
A2 - Rosa, Agostinho
A2 - Madani, Kurosh
A2 - Filipe, Joaquim
A2 - Cadenas, Jose M.
A2 - Merelo, Juan Julian
A2 - Filipe, Joaquim
PB - SciTePress
T2 - 7th International Joint Conference on Computational Intelligence, IJCCI 2015
Y2 - 12 November 2015 through 14 November 2015
ER -