ABSTRACT 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. INDEX TERMS Quaternion, color image, fractional Zernike moments, image forgery detection.
Some more recent works about image forgery detection also opens up forensic ideas for the detection of seam carving, such as a robust copy-move forgery detection algorithm proposed by Chen et al. REF , which considers the FrQZMs as a feature, and a modified PatchMatch algorithm as a feature-matching algorithm.
Fractional Quaternion Zernike Moments for Robust Color Image Copy-Move Forgery Detection
IEEE Access
IEEE Access
Computer Science