research-article

Detecting Non-Aligned Double JPEG Compression Based on Amplitude-Angle Feature

Authors:

Sunil Kr. JhaAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 4

Article No.: 138, Pages 1 - 18

https://doi.org/10.1145/3464388

Published: 12 November 2021 Publication History

Abstract

Due to the popularity of JPEG format images in recent years, JPEG images will inevitably involve image editing operation. Thus, some tramped images will leave tracks of Non-aligned double JPEG (NA-DJPEG) compression. By detecting the presence of NA-DJPEG compression, one can verify whether a given JPEG image has been tampered with. However, only few methods can identify NA-DJPEG compressed images in the case that the primary quality factor is greater than the secondary quality factor. To address this challenging task, this article proposes a novel feature extraction scheme based optimized pixel difference (OPD), which is a new measure for blocking artifacts. Firstly, three color channels (RGB) of a reconstructed image generated by decompressing a given JPEG color image are mapped into spherical coordinates to calculate amplitude and two angles (azimuth and zenith). Then, 16 histograms of OPD along the horizontal and vertical directions are calculated in the amplitude and two angles, respectively. Finally, a set of features formed by arranging the bin values of these histograms is used for binary classification. Experiments demonstrate the effectiveness of the proposed method, and the results show that it significantly outperforms the existing typical methods in the mentioned task.

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Index Terms

Detecting Non-Aligned Double JPEG Compression Based on Amplitude-Angle Feature
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Image processing
  2. Machine learning
    1. Machine learning algorithms
      1. Feature selection

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 17, Issue 4

November 2021

529 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3492437

Editor:
Alberto Del Bimbo
University of Firenze, Italy

Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 November 2021

Accepted: 01 May 2021

Revised: 01 January 2021

Received: 01 June 2020

Published in TOMM Volume 17, Issue 4

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Funding Sources

National Natural Science Foundation of China
National Key R & D Program of China
plan for Scientific Talent of Henan Province
Post graduate Research & Practice Innvoation Program of Jiang su Province
Priority Academic Program Development of Jiang su Higher Education Institutions (PAPD)

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https://dl.acm.org/doi/10.1145/3635152
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