Author(s): ESMAEEL FATEMI BEHBAHANI | AZADEH BASTANI
Journal: International Journal of Engineering Science and Technology
ISSN 0975-5462
Volume: 3;
Issue: 7;
Start page: 5466;
Date: 2011;
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Keywords: face recognition | orthogonal moments | Neural Networks
ABSTRACT
In this paper a new face recognition method has been introduced. By this method face features have been extracted by pseudo-Zernike moments (PZM).Then a probabilistic neural network has applied to classify thesemoments as feature vectors. Moment features are invariant under scaling, translation, rotation and reflection. Probabilistic Neural Networks have fast computational time. Results show that PZM of order of 14 with PNN have the best performance among all the moments
Journal: International Journal of Engineering Science and Technology
ISSN 0975-5462
Volume: 3;
Issue: 7;
Start page: 5466;
Date: 2011;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: face recognition | orthogonal moments | Neural Networks
ABSTRACT
In this paper a new face recognition method has been introduced. By this method face features have been extracted by pseudo-Zernike moments (PZM).Then a probabilistic neural network has applied to classify thesemoments as feature vectors. Moment features are invariant under scaling, translation, rotation and reflection. Probabilistic Neural Networks have fast computational time. Results show that PZM of order of 14 with PNN have the best performance among all the moments
