Personal authentication using feature points on finger and palmar creases

Abstract

A new and practical method of reliable and real-time authentication is proposed. Finger geometry and feature extraction of the palmar flexion creases are integrated in a few numbers of discrete points for faster and robust processing. A video image of either palm, palm placed freely facing toward a near infrared video camera in front of a low-reflective board, is acquired. Fingers are brought together without any constraints. Discrete feature point involves intersection points of the three digital (finger) flexion creases on the four finger skeletal lines and intersection points of the major palmar flexion creases on the extended finger skeletal lines, and orientations of the creases at the points. These metrics define the feature vectors for matching. Matching results are perfect for 50 subjects so far. This point wise processing, 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.