Multimodal biometric system based on hand geometry and palm print texture

Abstract

This paper presents a multimodal biometric identification system based on the geometrical and palm print features of the human hand. The right hand images are acquired by a commercial scanner with a 150 dpi resolution. The geometrical features are obtained from the binarized images and consist on 15 measures. A support vector machines is used as verifier. The palm print texture is obtained by means of a 2D Gabor phase encoding scheme. A robust coordinate system is defined to make easier the image alignment. A Hamming distance and threshold are used for verifying the identity. A score and decision level fusion results have shown the improvement of the combined scheme.