会议专题

JPEG IMAGE SECURITY BY BLOCK SIZE ESTIMATION AND QUALITY FACTOR CLASSIFICATION

  Passive methods in compressed images forensics are more preferable than active ones like watermarking.In passive methods,the deviation of natural characteristics of the compressed image plays a key role in performance.In this paper,based on the blockiness effect and its corresponding discontinuity imposed on block edges,we propose a universal normalized feature for passive analyses.Using this feature,we devise a high-precision straightforward procedure for JPEG block size extraction,and a machine learning approach for JPEG quality factor estimation.We also show that by extracting the messiness parameter of the image and designing a two-stage classifier,it is possible to boost the classification performance.Our simulation results validate the accuracy and efficiency of the proposed scheme.

Compressed image Security JPEG quality factor JPEG block size classification

Masoud Attarifar Mohammadamin Baniasadi

School of Electrical and Computer Engineering College of Engineering,University of Tehran,Tehran,Iran

国际会议

第九届网络分布式计算与知识发现国际会议( 2017 International Conference on Cyber-enabled distributed computing and knowledge discovery)

南京

英文

118-121

2017-10-12(万方平台首次上网日期,不代表论文的发表时间)