Orientation histograms for face recognition

Authors:
Friedhelm Schwenker;Andreas Sachs;Günther Palm;Hans A. Kestler
Affiliations:
Department of Neural Information Processing, University of Ulm, Ulm;Department of Neural Information Processing, University of Ulm, Ulm;Department of Neural Information Processing, University of Ulm, Ulm;Department of Neural Information Processing, University of Ulm, Ulm
Venue:
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
Year:
2006

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Abstract

In this paper we present a method to recognize human faces based on histograms of local orientation. Orientation histograms were used as input feature vectors for a k-nearest neigbour classifier. We present a method to calculate orientation histograms of n×n subimages partitioning the 2D-camera image with the segmented face. Numerical experiments have been made utilizing the Olivetti Research Laboratory (ORL) database containing 400 images of 40 subjects. Remarkable recognition rates of 98% to 99% were achieved with this extremely simple approach.