Paper ID: 2204.00305

Face identification by means of a neural net classifier

Virginia Espinosa-Duro, Marcos Faundez-Zanuy

This paper describes a novel face identification method that combines the eigenfaces theory with the Neural Nets. We use the eigenfaces methodology in order to reduce the dimensionality of the input image, and a neural net classifier that performs the identification process. The method presented recognizes faces in the presence of variations in facial expression, facial details and lighting conditions. A recognition rate of more than 87% has been achieved, while the classical method of Turk and Pentland achieves a 75.5%.

Submitted: Apr 1, 2022