Compression of personal identification pictures using vector quantization with facial feature correction

被引:9
作者
Hu, JH
Wang, RS
Wang, Y
机构
[1] Polytechnic University, Department of Electrical Engineering, 6 Metrotech Center, Brooklyn
[2] Department of Electronic Engineering, Shanghai Jiao Tong University
[3] Department of Electrical Engineering, Polytechnic University, Brooklyn, NY
[4] Tamkang University, Tamsui
[5] Chung Yuan Christian University, Chungli
[6] Tsinghua University, Beijing
[7] University of California, Santa Barbara, CA
[8] Polytechnic University, Brooklyn, NY
关键词
visual communications and image processing; facial image compression; facial feature detection; vector quantization;
D O I
10.1117/1.600878
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper describes a feature-correction two-stage vector quantization (FC2VQ) algorithm for the compression of photo ID pictures. The FC2VQ method treats different regions in a facial image differently. A region of facial features (ROFF), containing the eyes and the mouth, is detected and rendered more accurately than the rest of the image. The technique can compress a 128 x 128 x 8-bit (16,384 bytes total) ID image to an average size of 350 bytes. The quality of the compressed images is far superior to that obtained by other methods, including the JPEG standard, at similar compression ratios.
引用
收藏
页码:198 / 203
页数:6
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