A biometric palm print authorization system using local feature

Biometrics is an automated way of recognizing a person based on the physiological and behavioral characteristics. Such person characteristics are unique and distinct from one another. The well practiced and accepted physiological characteristics are face, finger, iris and palm print. And also the behavioral characteristics are signature, gesture, speech etc. are to be incorporated to design and develop multi-modal biometric recognition systems. This experimental paper is based on palm print physiological characteristics of biometric person recognition systems. The person recognition based on palm print characteristics are known to be robust and user friendly in terms of feature enrollment and overall access of the recognition system. In this paper, a novel method is proposed for personal identification using statistical palm print features. The palm print images are enhanced in a way to extract statistical features and based on this feature selection; the matching score of the user based palm prints sample is proposed.