A Multimodal Biometric Recognition of Touched Fingerprint and Finger-Vein

Multimodal biometric systems have been widely used to overcome the limitation of unimodal biometric systems and to achieve high recognition accuracy. However, users feel inconvenience because most of the multimodal systems require several steps in order to acquire multimodal biometric data, which also requires the specific behaviors of users. In this research, we propose a new multimodal biometric recognition of touched fingerprint and finger-vein. This paper is novel in the following four ways. First, we can get a fingerprint and a finger-vein image at the same time by the proposed device, which acquires the fingerprint and finger-vein images from the first and second knuckles of finger, respectively. Second, the device´s size is so small that we can adopt it on a mobile device, easily. Third, fingerprint recognition is done based on the minutia points of ridge area and finger-vein recognition is performed based on local binary pattern (LBP) with appearance information of finger area. Fourth, based on decision level fusion, we combined two results of fingerprint and finger-vein recognition. Experimental results confirmed the efficiency and usefulness of the proposed method.