New developments in color image tampering detection

Patchara Sutthiwan, Yun-Qing Shi, Jing Dong, Tieniu Tan, Tian Tsong Ng

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

20 Scopus citations

Abstract

In this paper, an efficient framework for passive-blind color image tampering detection is presented. Statistical features are extracted from a given test image and a set of 2-D arrays derived by applying multi-size block discrete cosine transform to the given test image. Image features are extracted from Cr channel, a chroma channel in YCbCr color space, because of its observed sensitivity to color image tampering. A support vector machine is employed to evaluate the effectiveness of image features over a color image dataset recently established for tampering detection. Boosting feature selection is applied to having feature dimensionality reduced so as to make detection accuracy generalizable and computational complexity decreased. Experimental results have demonstrated that the proposed framework applied to the aforementioned dataset outperforms the state of the arts by distinct margins.

Original languageEnglish (US)
Title of host publicationISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
Subtitle of host publicationNano-Bio Circuit Fabrics and Systems
Pages3064-3067
Number of pages4
DOIs
StatePublished - Aug 31 2010
Event2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France
Duration: May 30 2010Jun 2 2010

Other

Other2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
CountryFrance
CityParis
Period5/30/106/2/10

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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