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Digital Image Tamper Detection Techniques - A Comprehensive Study

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arxiv 1306.6737 v1 pith:2PHYJM2K submitted 2013-06-28 cs.CR cs.CV

classification cs.CRcs.CV
keywords digitalimagedetectionphotographstamperconventionalcostevidences
verification ladder T0 review T1 audit T2 compute T3 formal
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Photographs are considered to be the most powerful and trustworthy media of expression. For a long time, those were accepted as proves of evidences in varied fields such as journalism, forensic investigations, military intelligence, scientific research and publications, crime detection and legal proceedings, investigation of insurance claims, medical imaging etc. Today, digital images have completely replaced the conventional photographs from every sphere of life but unfortunately, they seldom enjoy the credibility of their conventional counterparts, thanks to the rapid advancements in the field of digital image processing. The increasing availability of low cost and sometimes free of cost image editing software such as Photoshop, Corel Paint Shop, Photoscape, PhotoPlus, GIMP and Pixelmator have made the tampering of digital images even more easier and a common practice. Now it has become quite impossible to say whether a photograph is a genuine camera output or a manipulated version of it just by looking at it. As a result, photographs have almost lost their reliability and place as proves of evidences in all fields. This is why digital image tamper detection has emerged as an important research area to establish the authenticity of digital photographs by separating the tampered lots from the original ones. This paper gives a brief history of image tampering and a state-of-the-art review of the tamper detection techniques.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 23 citations worldwide. Full citation record

  1. VisGuard: Securing Visualization Dissemination through Tamper-Resistant Data Retrieval

    cs.CV 2025-07 conditional novelty 5.0 of 10

    A steganography pipeline keeps a 324-bit metadata link readable in visualization images after up to 60% local tampering or about 80% cropping.

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