Forensics feature analysis in quaternion wavelet domain for distinguishing photographic images and computer graphics

Jinwei Wang, Ting Li, Yun Qing Shi, Shiguo Lian, Jingyu Ye

Research output: Contribution to journalArticlepeer-review

104 Scopus citations

Abstract

In this paper, a novel set of features based on Quaternion Wavelet Transform (QWT) is proposed for digital image forensics. Compared with Discrete Wavelet Transform (DWT) and Contourlet Wavelet Transform (CWT), QWT produces the parameters, i.e., one magnitude and three angles, which provide more valuable information to distinguish photographic (PG) images and computer generated (CG) images. Some theoretical analysis are done and comparative experiments are made. The corresponding results show that the proposed scheme achieves 18 percents’ improvements on the detection accuracy than Farid’s scheme and 12 percents than Özparlak’s scheme. It may be the first time to introduce QWT to image forensics, but the improvements are encouraging.

Original languageEnglish (US)
Pages (from-to)23721-23737
Number of pages17
JournalMultimedia Tools and Applications
Volume76
Issue number22
DOIs
StatePublished - Nov 1 2017

All Science Journal Classification (ASJC) codes

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications

Keywords

  • Contourlet wavelet transform
  • Discrete wavelet transform
  • Feature comparison
  • Forensics
  • Quaternion wavelet transform

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