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http://dx.doi.org/10.14400/JDC.2015.13.6.151

Authentication Performance Optimization for Smart-phone based Multimodal Biometrics  

Moon, Hyeon-Joon (School of Computer Science and Engineering, Sejong University)
Lee, Min-Hyung (School of Mechanical and Aerospace Engineering, Sejong University)
Jeong, Kang-Hun (School of Computer Science and Engineering, Sejong University)
Publication Information
Journal of Digital Convergence / v.13, no.6, 2015 , pp. 151-156 More about this Journal
Abstract
In this paper, we have proposed personal multimodal biometric authentication system based on face detection, recognition and speaker verification for smart-phone environment. Proposed system detect the face with Modified Census Transform algorithm then find the eye position in the face by using gabor filter and k-means algorithm. Perform preprocessing on the detected face and eye position, then we recognize with Linear Discriminant Analysis algorithm. Afterward in speaker verification process, we extract the feature from the end point of the speech data and Mel Frequency Cepstral Coefficient. We verified the speaker through Dynamic Time Warping algorithm because the speech feature changes in real-time. The proposed multimodal biometric system is to fuse the face and speech feature (to optimize the internal operation by integer representation) for smart-phone based real-time face detection, recognition and speaker verification. As mentioned the multimodal biometric system could form the reliable system by estimating the reasonable performance.
Keywords
Modified Census Transform; Face Authentication; Mel Frequency Cepstral Coefficient; Dynamic Time Warping; Multimodal Biometrics;
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