A Rotational- and Translational-Invariant Palmprint Recognition System

Abstract

Computer-aided personal recognition is becoming increasingly important in our information society. Biometric identification is an emerging technology that can solve security problems in our networked society. As the important implementation of biometric technology, palmprint verification is one of the most reliable personal identification methods. Human palmprint recognition has become an active area of research over the last decade. In this paper, a new approach to the palmprint preprocessing phase is presented. In real-time palmprint verification the input subject to the scanner for image acquisition may suffer rotational as well as translational variation. Because while the user puts his/her palm on the scanner, the angle and position of the palm may change. So, different images are acquired by the scanner according to the input each time. But in our paper we have suggested a rotational- as well as translationalinvariant scheme by which the above problem can be overcome while preprocessing the image before the feature extraction of the palmprint. With several palmprint images, we tested our proposed preprocessing system and the experimental results found good.