JPEG IMAGE SECURITY BY BLOCK SIZE ESTIMATION AND QUALITY FACTOR CLASSIFICATION

摘要：

　　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.

关键词： Compressed image Security JPEG quality factor JPEG block size classification

作者: Masoud Attarifar Mohammadamin Baniasadi

作者单位: School of Electrical and Computer Engineering College of Engineering,University of Tehran,Tehran,Iran

会议类型: 国际会议

会议名称: 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)

会议地点: 南京

会议语种:英文

页码: 118-121

在线出版日期: 2017-10-12（万方平台首次上网日期，不代表论文的发表时间）