  This paper describes a hand geometry biometric identification system. We have
acquired a database of 22 people, 10 acquisitions per person, using a
conventional document scanner. We propose a feature extraction and classifier.
The experimental results reveal a maximum identification rate equal to 93.64%,
and a minimum value of the detection cost function equal to 2.92% using a multi
layer perceptron classifier.
