Discrete finger and palmar feature extraction for personal authentication

A new method of a reliable and real-time authentication is proposed Finger geometry and feature extraction of the palmar flexion creases are integrated in discrete points of characteristics. A video image of either palm, palm placed freely facing toward a video camera in front of a low-reflective board, is acquired Fingers are brought together without any constraints. Discrete feature point extraction for each of the four fingers involves: intersection points of the three digital (finger) flexion creases on the finger skeletal line; skeletal lengths of the finger segments between the three creases; distances between the intersection points and the corresponding points of the adjacent fingers. Discrete feature extraction for the palm involves: intersection points of the major palmar flexion creases on tire extended finger skeletal line; orientation of the crease at each point of the intersection. These metrics define the feature vectors for matching. Matching results are perfect for 50 subjects so far. This point wise integration of the finger and palmar feature extraction, extracting enough feature from non contacting video image, requiring no time-consumptive palm print image analysis, and requiring less than one second processing time, will contribute to a real-time and reliable authentication.