Multimodal Biometric System Based on the Recognition of Face and Both Irises
Author(s) -
Yeong Gon Kim,
Kwang Yong Shin,
Eui Chul Lee,
Kang Ryoung Park
Publication year - 2012
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/50869
Subject(s) - computer science , biometrics , artificial intelligence , computer vision , iris recognition , face (sociological concept) , iris (biosensor) , fingerprint (computing) , modality (human–computer interaction) , facial recognition system , pattern recognition (psychology) , social science , sociology
The performance of unimodal biometric systems (based on a single modality such as face or fingerprint) has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises’ recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near‐infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods
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