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Automatic Forgery Localization via Artifacts Analysis of JPEG and Resampling

  • Hongbin Wei
  • Heng YaoEmail author
  • Chuan Qin
  • Zhenjun Tang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 895)

Abstract

With the availability of highly sophisticated editing tools, the authenticity of digital images has now become questionable. The level of image tampering is getting higher and higher, and the tampering procedures become more and more complicated. To recognize the tampering area of the original image, the tampered image is usually executed a series of post-processing. This behavior has greatly increased the difficulty of forgery detection. In this paper, a blind JPEG image forgery detection and localization technique based on JPEG and resampling artifacts analysis is proposed. The process of tampering is to first tamper with JPEG images by bitmaps. Then original JPEG image and tampered area are manipulated by a series of operations, that is, the image is enlarged and then saved as JPEG. A novel tampering localization method is presented based on resampling and JPEG blockness artifacts. Theoretical analysis and experimental results show that the proposed method can effectively identify and locate the tampered region of a spliced image with a JPEG-resampling-JPEG operation chain.

Keywords

Digital forensics JPEG compression Resampling effect Operation chain 

Notes

Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (61702332, 61672354, 61562007), Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (MIMS16-03), the Guangxi Natural Science Foundation (2017GXNSFAA198222), the Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing. The authors would like to thank the anonymous reviewers for their helpful comments.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Hongbin Wei
    • 1
  • Heng Yao
    • 1
    • 2
    Email author
  • Chuan Qin
    • 1
  • Zhenjun Tang
    • 2
  1. 1.School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghaiChina
  2. 2.Guangxi Key Lab of Multi-source Information Mining and SecurityGuangxi Normal UniversityGuilinChina

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