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Orientation Histograms for Face Recognition

  • Friedhelm Schwenker
  • Andreas Sachs
  • Günther Palm
  • Hans A. Kestler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4087)

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.

Keywords

Orientation histograms Face recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Friedhelm Schwenker
    • 1
  • Andreas Sachs
    • 1
  • Günther Palm
    • 1
  • Hans A. Kestler
    • 1
  1. 1.Department of Neural Information ProcessingUniversity of UlmUlm

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