Rake transform and edge statistics for image forgery detection

Patchara Sutthiwan, Yun Q. Shi, Wei Su, Tian Tsong Ng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

In this paper, an effective framework for passive-blind color image forgery detection is proposed. It is a combination of image features extracted from image luminance by applying a rake-transform and from image chroma by using edge statistics. The efficacy of the image features has been tested over two color image datasets established for tampering detection. The proposed framework outweighs the state of the arts over the small-scale dataset, and performs well on the newly established large-scaled dataset (likely the first reported test result on this dataset). The initial tests on some real image forgery cases available in the website and those reported in the literature on image composition with advanced image and vision technologies indicate the promise possessed as well as the challenge faced by the community of image forgery detection.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Multimedia and Expo, ICME 2010
Pages1463-1468
Number of pages6
DOIs
StatePublished - Nov 22 2010
Event2010 IEEE International Conference on Multimedia and Expo, ICME 2010 - Singapore, Singapore
Duration: Jul 19 2010Jul 23 2010

Publication series

Name2010 IEEE International Conference on Multimedia and Expo, ICME 2010

Other

Other2010 IEEE International Conference on Multimedia and Expo, ICME 2010
Country/TerritorySingapore
CitySingapore
Period7/19/107/23/10

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Software

Keywords

  • Boosting feature selection
  • Color image forgery detection
  • Color image tampering detection
  • Edge statistics
  • Rake transform
  • Reconstructed image

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