Locating geometrical descriptors for hand biometrics in a contactless environment

This paper proposes an innovative contactless hand geometry recognition system. We present a novel hand tracking approach to automatically detect and capture the geometrical features of the hand from low resolution video stream. No constraint is imposed and the subject can place his/her hand naturally on top of the sensor without touching any device. Conventional hand geometry systems require fairly precise positioning of the hand in order to obtain accurate measures of the hand. However, the proposed contactless approach does not fix any guidance pegs to help placing the hand at the right position when the image is acquired. As a result, the hand image may appear larger when the hand is placed near the sensor, and vice versa. Besides, the hand can be positioned at different angles. In other words, there is no way to obtain standard and constant hand measurements from this contactless setting. This research aims to deal with this complication when we have to get accurate measurements of the hand from images with varying sizes and directed at different orientations. Experiments show that our proposed method offers promising result for hand geometry recognition in a real-time contactless environment.