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Related Experiment Video

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Evolutionary History of Life on Earth
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JPEG compression history detection based on detail deviation.

Bo Wang1, Ya Bin Li1, Jian Xiang Zhao1

  • 1School of Information and Communication Engineering, Dalian University of Technology, Dalian, 116024, China.

Mathematical Biosciences and Engineering : MBE
|September 11, 2019
PubMed
Summary

This study introduces a new method for detecting JPEG compression history in images by analyzing image information loss. The technique efficiently identifies image tampering by examining changes in zero coefficients.

Keywords:
JPEG coefficientbitmapcompression historyimage information loss

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Area of Science:

  • Digital Image Forensics
  • Computer Vision
  • Information Security

Background:

  • Image authenticity is vital for legal and security purposes.
  • Detecting JPEG compression history can reveal image tampering.
  • Existing methods for JPEG compression detection have limitations.

Purpose of the Study:

  • To propose a lightweight and reliable method for detecting JPEG compression history.
  • To identify image tampering by analyzing information loss during compression.
  • To improve the accuracy of JPEG compression detection.

Main Methods:

  • Proposing a novel feature based on the decreasing percentage of zero coefficients.
  • Estimating the original image and re-compressing it to analyze JPEG coefficients.
  • Calculating image information loss to determine compression history.
  • Utilizing the relationship between quality factor and zero coefficient percentage.

Main Results:

  • The proposed method demonstrates high reliability in detecting JPEG compression history.
  • Experimental results show superior performance compared to existing methods.
  • The method effectively identifies the possibility of image tampering.

Conclusions:

  • The developed method offers an efficient approach to JPEG compression detection.
  • Analyzing image information loss is a viable strategy for forensic analysis.
  • This technique enhances the security and trustworthiness of digital images.