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Double JPEG Compression Detection Based on Fusion Features

  • Fulong Yang
  • Yabin Li
  • Kun Chong
  • Bo Wang
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 226)

Abstract

Detection of double JPEG compression plays an increasingly important role in image forensics. This paper mainly focuses on the situation where the images are aligned double JPEG compressed with two different quantization tables. We propose a new detection method based on the fusion features of Benford features and likelihood probability ratio features in this paper. We believe that with the help of likelihood probability ratio features, our fusion features can expose more artifacts left by double JPEG compression, which lead to a better performance. Comparative experiments have been carried out in our paper, and experimental result shows our method outperforms the baseline methods, even when one of the quality factors is pretty high.

Keywords

Double compression detection DCT coefficients Likelihood probability ratio features Benford features 

Notes

Acknowledgments

This work is supported by the National Science Foundation of China (No. 61502076) and the Scientific Research Project of Liaoning Provincial Education Department (No. L2015114).

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.School of Information and Communication EngineeringDalian University of TechnologyDalianPeople’s Republic of China

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