A Palmprint Identification System using Robust Discriminant Orientation Code

Abstract

This paper presents a palmprint recognition system in which we propose a novel acquisition device and a Robust Discriminant Orientation Code, called RDORIC, for palmprint identification. In order to get the clear line features, the device is designed to capture the palmprint images under Green illuminations. To extract RDORIC feature, we present the algorithm which includes two main steps: (1) Palm line orientation map computation and (2) Discriminant feature extraction of the orientation map. In the first step, positive orientation and negative orientation maps are computed by applying the modified finite Radon transform (MFRAT). In the second step, the grid-sampling based 2DLDA, called Grid-LDA, is used to remove redundant information of orientation maps and form a class-separable code more suitable for palmprint identification. The experimental results on the database of our lab and the public database of Hong Kong Polytechnic University (PolyU) show that our technique provides a very robust orientation representation for recognition and demonstrate the feasibility of the proposed system.