Personal Verification Using Palmprint and Hand Geometry Biometric

A new approach for the personal identification using hand images is presented. This paper attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike other bimodal biometric systems, the users do not have to undergo the inconvenience of using two different sensors since the palmprint and hand geometry features can be acquired from the same image, using a digital camera, at the same time. Each of these gray level images are aligned and then used to extract palm print and hand geometry features. These features are then examined for their individual and com bined performances. The image acquisition setup used in this work is inherently simple and it does not employ any special illumination nor does it use any pegs to cause any inconvenience to the users. Our experimental results on the image dataset from 100 users confirm the utility of combining hand geometry features with those from palmprints using a simple image acquis ition setup.