Identifying computer graphics using HSV color model and statistical moments of characteristic functions

Wen Chen, Yun Q. Shi, Guorong Xuan

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

124 Scopus citations

Abstract

Computer graphics generated by advanced rendering software come to appear so photorealistic that it has become difficult for people to visually differentiate them from photographic images. Consequently, modern computer graphics may be used as a convincing form of image forgery. Therefore, identifying computer graphics has become an important issue in image forgery detection. In this paper, a novel approach to distinguishing computer graphics from photographic images is introduced. The statistical moments of characteristic function of the image and wavelet subbands are used as the distinguishing features. In addition, we investigate the influence of different image color representations on the feature effectiveness. Specifically, the efficiency of using RGB and HSV color models is investigated. The experiments have shown that the features extracted from HSV color space, which decouples brightness from chromatic components, have demonstrated better performance than that from RGB color model.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
PublisherIEEE Computer Society
Pages1123-1126
Number of pages4
ISBN (Print)1424410177, 9781424410170
DOIs
StatePublished - Jan 1 2007
EventIEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, China
Duration: Jul 2 2007Jul 5 2007

Publication series

NameProceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

Other

OtherIEEE International Conference onMultimedia and Expo, ICME 2007
Country/TerritoryChina
CityBeijing
Period7/2/077/5/07

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Software

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