Minutiae-Based Offline Palmprint Identification System

As a noteworthy biometric technology, offline palm-print identification plays a very important role in the application of social security. Given a palm-print scanned by a digital instrument, offline palm-print identification needs to perform robust feature matching because of the rotation and distortion existed in input. In our paper we design and implement a minutiae-based offline palm-print identification system, which can realize the unrestricted matching between the complete palm-print and misshapen palm-print, therefore being able to identify of the owner of the palm-print. The paper presents the location, image enhancement, thinning, minutia feature extraction and feature matching in detail. The system framework and processing approach can overcome various issues caused by the limitation of condition in palm-print acquisition and achieve stable results. The experiment based on the true date test proves the effectiveness and efficiency of the work in this article.