A Codebook Design Method for Robust VQ-Based Face Recognition Algorithm
Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi
DOI: 10.4236/jsea.2010.32015   PDF    HTML     5,250 Downloads   10,157 Views   Citations


In this paper, we present a theoretical codebook design method for VQ-based fast face recognition algorithm to im-prove recognition accuracy. Based on the systematic analysis and classification of code patterns, firstly we theoretically create a systematically organized codebook. Combined with another codebook created by Kohonen’s Self-Organizing Maps (SOM) method, an optimized codebook consisted of 2×2 codevectors for facial images is generated. Experimental results show face recognition using such a codebook is more efficient than the codebook consisted of 4×4 codevector used in conventional algorithm. The highest average recognition rate of 98.6% is obtained for 40 persons’ 400 images of publicly available face database of AT&T Laboratories Cambridge containing variations in lighting, posing, and expressions. A table look-up (TLU) method is also proposed for the speed up of the recognition processing. By applying this method in the quantization step, the total recognition processing time achieves only 28 msec, enabling real-time face recognition.

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Q. Chen, K. Kotani, F. Lee and T. Ohmi, "A Codebook Design Method for Robust VQ-Based Face Recognition Algorithm," Journal of Software Engineering and Applications, Vol. 3 No. 2, 2010, pp. 119-124. doi: 10.4236/jsea.2010.32015.

Conflicts of Interest

The authors declare no conflicts of interest.


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