Title :
Color personal ID photo compression based on object segmentation
Author :
Qiuyu, Zhu ; Suozhong, Wang
Author_Institution :
Sch. of Commun. & Inf., Shanghai Univ., China
Abstract :
The paper studies color personal identification photo compression based on object segmentation. Using an object pattern recognition method, a personal ID photo is divided into three regions - background, head-and-shoulder region and facial region. Different regions have different image qualities. After adopting the Freeman chain code description and its arithmetic coding of background boundary, background adaptive gray padding, bit-plane shift quality graded compression algorithm, and JPEG-2000 based wavelet transform and EBCOT coding scheme, a good result that is better than the standard JPEG-2000 is obtained.
Keywords :
data compression; image coding; image colour analysis; image segmentation; object recognition; wavelet transforms; Freeman chain code description; JPEG-2000 based wavelet transform; arithmetic coding; background adaptive gray padding; background boundary; bit-plane shift quality graded compression algorithm; color personal identification photo compression; facial region; head-and-shoulder region; image qualities; object pattern recognition method; object segmentation; Arithmetic; Compression algorithms; Image coding; Image quality; Image storage; Object segmentation; Pattern recognition; Transform coding; Vector quantization; Wavelet coefficients;
Conference_Titel :
Communications, Computers and signal Processing, 2005. PACRIM. 2005 IEEE Pacific Rim Conference on
Print_ISBN :
0-7803-9195-0
DOI :
10.1109/PACRIM.2005.1517352
