A novel representation of palm-print for recognition

Abstract

This paper proposes a novel palm-print feature extraction technique which is based on binarising the difference of Discrete Cosine Transform coefficients of overlapping circular strips. The binary features of palm-print are matched using Hamming distance. The system is evaluated using PolyU database consisting of 7,752 images. A procedure to extract palm-print for PolyU dataset is proposed and found to extract larger area compared to preprocessing technique in [1]. Variation in brightness of the extracted palm-print is corrected and the contrast of its texture is enhanced. Compared to the systems in [1, 2], the proposed system achieves higher Correct Recognition Rate (CRR) of 100 % with lower Equal Error Rate (EER) of 0.0073% at low computational cost. © 2011 Springer-Verlag Berlin Heidelberg.