Q. Chen, K. Kotani, F. Lee, and T. Ohmi, “Face recogni-tion using codebook designed by code classification,” 2006 IEEE International Conference on Signal and Image Processing, Hubli, India, pp. 397–401, December 2006.

has been cited by the following article:

• TITLE: A Codebook Design Method for Robust VQ-Based Face Recognition Algorithm

  AUTHORS: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

  KEYWORDS: Face Recognition, Vector Quantization (VQ), Codebook Design, Code Classification, Histogram Method

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.3 No.2, March 2, 2010

  ABSTRACT: 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.