Color personal ID photo compression based on object segmentation

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.