Fractional quaternion zernike moments for robust color image copy-move forgery detection

Beijing Chen, Ming Yu, Qingtang Su, Hiuk Jae Shim, Yun Qing Shi

Research output: Contribution to journalArticlepeer-review

87 Scopus citations


In this paper, fractional Zernike moments (FrZMs) for complex signals are generalized to fractional quaternion Zernike moments (FrQZMs) for quaternion signal processing in a holistic manner by the quaternion algebra. We first present the definition of FrQZMs and an efficient implementation algorithm for speeding up the computation of FrQZMs through FrZMs of each component of the quaternion signal. The performance of the proposed FrQZMs is evaluated by considering robust color image copy-move forgery detection. The proposed robust copy-move forgery-detection algorithm considers the FrQZMs as a feature and a modified PatchMatch algorithm as a feature matching algorithm. Experimental results on two publicly available data sets (FAU and GRIP data set) have demonstrated that the proposed FrQZM-based algorithm can achieve an overall better performance than the state-of-the-art algorithms, especially in some additional operation cases.

Original languageEnglish (US)
Article number8471093
Pages (from-to)56637-56646
Number of pages10
JournalIEEE Access
StatePublished - 2018

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering


  • Quaternion
  • color image
  • fractional Zernike moments
  • image forgery detection


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