Fractional-order orthogonal Chebyshev Moments and Moment Invariants for image representation and pattern recognition

作者：

Highlights：

• Introducing a new set of fractional-order moments for image representation.

• Constructing a set of fractional-order moment invariants for pattern recognition.

• Discussing the computational aspects of the proposed fractional-order moments and moment invariants.

• Providing numerical experiments to demonstrate their validity and superiority.

摘要

•Introducing a new set of fractional-order moments for image representation.•Constructing a set of fractional-order moment invariants for pattern recognition.•Discussing the computational aspects of the proposed fractional-order moments and moment invariants.•Providing numerical experiments to demonstrate their validity and superiority.

论文关键词：Fractional-order orthogonal moments,Fractional-order Chebyshev polynomials,Moment invariants,Image representation,Pattern recognition,Fast and accurate computation

论文评审过程：Received 30 October 2017, Revised 17 September 2018, Accepted 3 October 2018, Available online 3 October 2018, Version of Record 10 October 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.10.001