3D image analysis by separable discrete orthogonal moments based on Krawtchouk and Tchebichef polynomials

作者：

Highlights：

• This paper introduces new sets of separable discrete moments for 3D image analysis.

• This paper provides the process for deriving 3D moment invariants (scale, translation, rotation).

• Numerical experiments are performed to demonstrate its validity and superiority.

摘要

•This paper introduces new sets of separable discrete moments for 3D image analysis.•This paper provides the process for deriving 3D moment invariants (scale, translation, rotation).•Numerical experiments are performed to demonstrate its validity and superiority.

论文关键词：3D image analysis,Separable moments,Moment invariants,Numerical stability,Object classification,Multivariate discrete orthogonal polynomials,Krawtchouk moments,Tchebichef moments

论文评审过程：Received 12 February 2017, Revised 3 May 2017, Accepted 7 June 2017, Available online 10 June 2017, Version of Record 20 June 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.06.013