This paper presents a new approach for personal authentication using hand images. The proposed method attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike prior bimodal biometric systems, the users do not have to undergo the inconvenience of using two different sensors in our system since the palmprint and hand geometry images are acquired simultaneously using a single camera. The palmprint and handshape images are used to extract salient features and are then examined for their individual and combined verification performances. The image acquisition setup used here is inherently simple and it does not employ any special illumination nor does it use any alignment pegs to cause any inconvenience to the users. Our experiments on an image database of 100 users achieve promising results and suggest that the fusion of matching scores can achieve better performance than the fusion at representation.