Limitation investigation toward lips recognition
Yun-Fu Liu, Chao‐Yu Lin, Jing-Ming Guo · 2012
In this paper, the impact of the lips for facial recognition is investigated. In the first stage of the proposed system, a Fast Box Filtering (FBF) is proposed to generate a noise-free source with high processing efficiency. Afterward, five various mouth corners are detected though the proposed system, in which it is also able to resist beard and rotation problems. For the feature extraction, two geometric ratios and 10 parabolic related parameters are adopted for further recognition through the Support Vector Machine (SVM). Experimental results demonstrate that when the number of subjects is fewer or equal to 36, the Correct Accept Rate (CAR) is greater than 98%, and the False Accept Rate (FAR) is smaller than 0.064% (CAR>;95.6%, FAR<;0.083%| #Subjects ≤ 54). Moreover, the processing speed of the overall system achieves 34.43 fps (frame/sec) which meets the real-time requirement.