A Codebook Design Method for Robust VQ-Based Face Recognition Algorithm
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that the 2×2 codebook created by proposed method
represent the features of the facial images more ade-
quately than conventional codebooks.
4.3 Processing Time
Processing time for single image in the face database of
AT&T Laboratories Cambridge [19] is about 57 msec
using a codebook of size 80, which is composed of 15
msec for pretreatment including filtering, block divi-
sion, and minimum intensity subtraction, 30 msec for
VQ processing, and 12 msec for database matching.
Furthermore, because a 2×2 codevector can be rep-
resented by an array of 4 dimensions, by utilizing the
table look-up (TLU) method in the VQ processing step,
the VQ processing time can be shorten to be about 1
msec, and the total running time will be 28 msec. It
means our fast recognition algorithm achieves real-
time face recognition.
5. Conclusions
In this paper, a theoretical codebook design method for
robust VQ-based face recognition algorithm is pro-
posed. Combining a systematically organized codebook
based on the classification of code patterns and another
codebook created by Kohonen’s Self-Organizing Maps
(SOM), an optimized codebook consisted of 2×2 code-
vectors for facial images is generated. Utilizing such a
codebook of size 80, the highest average recognition
rate of 98.6% is obtained for 40 persons’ 400 images of
the database of AT&T Laboratories Cambridge.
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