Lip-Sync Personal Authentication System Using Movement Feature of Lip

2013 ◽  
Author(s):  
Tatsuya Nakata ◽  
Masayuki Kashima ◽  
Kiminori Sato ◽  
Mutsumi Watanabe
Keyword(s):  
Lip Sync ◽  
Authentication System ◽  
Personal Authentication

Personal Authentication System using Remote Control Device and Pressure Distribution Sensor

2013 ◽  
Vol 133 (5) ◽  
pp. 1041-1046
Author(s):  
Yusuke Kajiwara ◽  
Keisuke Oshima ◽  
Munehiro Nakamura ◽  
Hidetaka Nambo ◽  
Haruhiko Kimura
Keyword(s):  
Remote Control ◽  
Pressure Distribution ◽  
Control Device ◽  
Authentication System ◽  
Personal Authentication

USER AUTHENTICATION USING FUSION OF FACE AND PALMPRINT

2009 ◽  
Vol 09 (02) ◽  
pp. 251-270 ◽  
Author(s):  
AJAY KUMAR ◽  
DAVID ZHANG
Keyword(s):  
Performance Improvement ◽  
User Authentication ◽  
Digital Camera ◽  
Performance Indices ◽  
Feed Forward Neural Network ◽  
Class Separation ◽  
Criterion Functions ◽  
Significant Performance ◽  
Authentication System ◽  
Personal Authentication

This paper presents a new method of personal authentication using face and palmprint images. The facial and palmprint images can be simultaneously acquired by using a pair of digital camera and integrated to achieve higher confidence in personal authentication. The proposed method of fusion uses a feed-forward neural network to integrate individual matching scores and generate a combined decision score. The significance of the proposed method is more than improving performance for bimodal system. Our method uses the claimed identity of users as a feature for fusion. Thus the required weights and bias on individual biometric matching scores are automatically computed to achieve the best possible performance. The experimental results also demonstrate that Sum, Max, and Product rule can be used to achieve significant performance improvement when consolidated matching scores are employed instead of direct matching scores. The fusion strategy used in this paper outperforms even its existing facial and palmprint modules. The performance indices for personal authentication system using two-class separation criterion functions have been analyzed and evaluated. The method proposed in this paper can be extended for any multimodal authentication system to achieve higher performance.

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