Hand Shape Geometry and Palmprint Features for the Personal Identification

Abstract

A new approach for the personal identification using hand images is presented. Two kinds of biometric indicators can be extracted from the low-resolution hand images; (i) palmprint features, which are composed of principal lines, wrinkles, minutiae, delta points, etc., and (ii) hand geometry features which include area/size of palm, length and width of fingers. The system is based on the images of the right hands of the subjects, captured by a flatbed scanner in an specific constrained pose. In a preprocessing stage of the algorithm, the silhouettes of hand images are registered. Hand geometry based biometric verification has proven to be the most suitable and acceptable biometrics trait for medium and low security applications.