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Título del libro: 2014 International Work Conference On Bio-Inspired Intelligence: Intelligent Systems For Biodiversity Conservation, Iwobi 2014 - Proceedings
Título del capítulo: Rotation distortions for improvement in face recognition with PCNC

Autores UNAM:
ERNST KUSSUL;
Autores externos:

Idioma:
Inglés
Año de publicación:
2014
Palabras clave:

Classification (of information); Face recognition; Image coding; Image retrieval; Neural networks; Support vector machines; Image database; Iterative closest point; Neural classifiers; Original images; Permutation coding; Rotation distortion; Training process; Airport security


Resumen:

face recognition is a very important task in security (airports, institutions, and so on) and authentication through photo tagging in social networks. We propose to improve face recognition with the Permutation Coding Neural Classifier (PCNC) using a special type of distortions of original images (for example, rotations) to train the neural network. We applied the distortions to the initial image database (the FRAV2D image database) and produced an extended rotated version of it that allowed us to improve the training process of PCNC neural classifier. The results obtained show a better recognition rate in comparison to Support Vector Machine (SVM) and Iterative Closest Point (ICP). © 2014 IEEE.


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