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IEEE Transactions on Pattern Analysis and Machine Intelligence
Biometrics: advanced identity verification
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Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
Cryptography and Network Security: Principles and Practice
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IEEE Transactions on Computers
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IEEE Transactions on Pattern Analysis and Machine Intelligence
LAFTER: Lips and Face Real-Time Tracker
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Initialized Eigenlip Estimator for Fast Lip Tracking Using Linear Regression
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
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Automatic Lip Tracking: Bayesian Segmentation and Active Contours in a Cooperative Scheme
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The use of Speech and Lip Modalities for Robust Speaker Verification under Adverse Conditions
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
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Computational Intelligence and Security
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Biometric systems are forms of technology that use unique human physical characteristics to automatically identify individuals. They have sensors to pick up physical characteristics, convert them into digital patterns, and compare them with patterns stored for individual identification. However, lip print recognition has been less developed than the recognition of other human physical attributes such as the fingerprint, voice patterns, retinal blood vessel patterns, or the face. Lip print recognition by a CCD camera has the merit of being linked with other recognition systems such as the retinal/iris eye and the face. A new method using multi-resolution architecture is proposed to recognize a lip print from pattern kernels. A set of pattern kernels is a function of some local lip print masks. This function converts the information from a lip print into digital data. Recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. Multi-resolution architecture allows us to reduce the false recognition rate from 15 to 4.7%. This paper shows that a lip print is sufficiently used by the measurements of biometric systems.