Palmprint based Verification System Robust to Occlusion using Low-order Zernike Moments of Sub-image

This paper proposes a palmprint based verification system using low-order Zernike moments of palmprint sub-images. The Zernike moments of corresponding sub-images of live and enrolled palmprint are matched using Euclidean distance for verification. An efficient weighted fusion technique to fuse matching scores of the sub-images is proposed. The palmprint is extracted from the hand image acquired using a low cost flat bed scanner. The extraction is robust to hand translation and rotation on the scanner. The proposed system is also robust to occlusion and can verify user the features of from non-occluded region. The system is tested on IITK, PolyU and CASIA databases of size 549, 5,239 and 7,752 hand images respectively.