Discrete Finger and Palmar Feature Extraction for Personal Authentication

Abstract

A practical method for a noncontacting and real-time feature extraction for personal authentication is proposed. The finger geometry and feature extraction of the palmar flexion creases are integrated into a small number of discrete points based on the anatomical observation. For a video image of either palm, a palm placed freely facing toward a video camera is acquired. The fingers are brought together, and the palm is straightened out to eliminate any constraints. The discrete feature points for the fingers involve intersection points of the three finger (digital) flexion creases on the four finger skeletal lines. The feature points for the palm involve intersection points of the major palmar flexion creases and/or prominent creases of the palm on the extended finger skeletal lines. The orientations of the creases at the intersection points are also extracted features to be matched. The matching results are perfect for about 500 palm samples from 50 subjects so far. This discrete point processing, requiring no time-consumptive palmprint image analysis and requiring less than one second processing time, will contribute to a noncontacting, real-time and reliable feature extraction, easily combinable with other traits, for the personal authentication.