TY - GEN
T1 - A multimodal biometric recognition of touched fingerprint and finger-vein
AU - Park, Young Ho
AU - Lee, Hyeon Chang
AU - Park, Kang Ryoung
AU - Tien, Dat Nguyen
AU - Lee, Eui Chul
AU - Kim, Sung Min
AU - Kim, Ho Chul
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Component
KW - Finger-vein recognition
KW - Fingerprint recognition
KW - Multimodal biometric
UR - http://www.scopus.com/inward/record.url?scp=80051861824&partnerID=8YFLogxK
U2 - 10.1109/CMSP.2011.57
DO - 10.1109/CMSP.2011.57
M3 - Conference contribution
AN - SCOPUS:80051861824
SN - 9780769543567
T3 - Proceedings - 2011 International Conference on Multimedia and Signal Processing, CMSP 2011
SP - 247
EP - 250
BT - Proceedings - 2011 International Conference on Multimedia and Signal Processing, CMSP 2011
T2 - 2011 International Conference on Multimedia and Signal Processing, CMSP 2011
Y2 - 14 May 2011 through 15 May 2011
ER -