Abstract

Moment and moment invariants as effective feature descriptors have been widely applied in image analysis, pattern recognition and computer vision applications. Scholars have demonstrated that fractional-order orthogonal moments outperform their corresponding moments in representing the fine details of a given image. To this end, we propose a new fractional-order orthogonal moments based on fractional-order weighted spherical Bessel polynomial in this paper, which is named as Fractional-order weighted Spherical Bessel-Fourier Moments (FrSBFMs). Moreover, to address the issue of color image analysis, FrSBFMs are integrated with quaternion theory to develop Quaternion FrSBFMs (QFrSBFMs). In addition, the rotation invariance and parameter α analysis of FrSBFMs and QFrSBFMs are discussed in detail. The experimental results show the effectiveness of the proposed FrSBFMs and QFrSBFMs in terms of image reconstruction capability, pattern recognition accuracy and zero-watermark verification.

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