Image analysis using separable two-dimensional discrete orthogonal moments

This paper presents three new separable 2-D discrete orthogonal moments. The kernel functions of the proposed Meixner Krawtchouk moments (MKM), Tchebichef-Charlier moments (TCM), and Meixner-Hahn moments (MHM) are mutually orthogonal and separable. Unlike the traditional 2-D discrete orthogonal moments, in the proposed separable 2-D discrete orthogonal moments, the kernel functions can be expressed as two separable terms by producing two different classical orthogonal polynomials of a variable. Specifically, the tense product of Meixner and Krawtchouk polynomials can be used to generate kernel functions for 2-D discrete orthogonal MKM. The global extraction capabilities of proposed moments are described by analyzing the reconstructed image´s accuracy. The experimental results show that these proposed moments have better image description capabilities.