Hand Geometry Based Recognition with a MLP Classifier

  • Marcos Faundez-Zanuy
  • Miguel A. Ferrer-Ballester
  • Carlos M. Travieso-González
  • Virginia Espinosa-Duro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)


This paper presents a biometric recognition system based on hand geometry. We describe a database specially collected for research purposes, which consists of 50 people and 10 different acquisitions of the right hand. This database can be freely downloaded. In addition, we describe a feature extraction procedure and we obtain experimental results using different classification strategies based on Multi Layer Perceptrons (MLP). We have evaluated identification rates and Detection Cost Function (DCF) values for verification applications. Experimental results reveal up to 100% identification and 0% DCF.


Mean Square Error Multi Layer Perceptrons Mean Absolute Difference Biometric System IEEE Aerospace 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Marcos Faundez-Zanuy
    • 1
  • Miguel A. Ferrer-Ballester
    • 2
  • Carlos M. Travieso-González
    • 2
  • Virginia Espinosa-Duro
    • 1
  1. 1.Escola Universitària Politècnica de Mataró (UPC)BarcelonaSpain
  2. 2.Dpto. de Señales y ComunicacionesUniversidad de Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

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