Radial Tchebichef Invariants for Pattern Recognition

This paper presents the mathematical framework of radial Tchebichef moment invariants, and investigates their feature representation capabilities for pattern recognition applications. The radial Tchebichef moments are constructed using the discrete orthogonal Tchebichef polynomials as the kernel, and they have a radial-polar form similar to that of Zernike moments. The discrete form of the moment transforms make them particularly suitable for image processing tasks. Experimental results showing the primary attributes such as invariance and orthogonality of the proposed moment functions are also given.