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An advanced texture analysis method for image sharpening detection

  • Feng Ding*
  • , Weiqiang Dong
  • , Guopu Zhu
  • , Yun Qing Shi
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Sharpening is a kind of basic yet widely utilized digital image processing techniques designed and utilized to pursue better image quality from human visual point of view. In image forensics it is required to detect this kind of operation. Huge progress has been made in this area in recent years. Overshoot artifact, as a unique phenomenon occurring on image edges after sharpening, is important in sharpening detection. In this paper, an advanced scheme for overshoot artifact determination is proposed to boost the detection performance in the case of mildor overshoot artifact-controlled sharpening, Several groups of experiments have been conducted to corroborate the new scheme possesses the best ability for blind sharpening detection regardless of the strength of overshoot artifact.

Original languageEnglish
Title of host publicationDigital-Forensics and Watermarking - 14th International Workshop, IWDW 2015, Revised Selected Papers
EditorsIsao Echizen, Hyoung Joong Kim, Yun-Qing Shi, Fernando Pérez-González
PublisherSpringer Verlag
Pages72-82
Number of pages11
ISBN (Print)9783319319599
DOIs
StatePublished - 2016
Externally publishedYes
Event14th International Workshop on Digital-Forensics and Watermarking, IWDW 2015 - Tokyo, Japan
Duration: 7 Oct 201510 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9569
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Workshop on Digital-Forensics and Watermarking, IWDW 2015
Country/TerritoryJapan
CityTokyo
Period7/10/1510/10/15

Keywords

  • Edge perpendicular binary code
  • Image forensics
  • Overshoot artifact
  • Sharpening detection

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