Skip to Main content Skip to Navigation
Journal articles

Image analysis by discrete orthogonal dual Hahn moments

Abstract : In this paper, we introduce a set of discrete orthogonal functions known as dual Hahn polynomials. The Tchebichef and Krawtchouk polynomials are special cases of dual Hahn polynomials. The dual Hahn polynomials are scaled to ensure the numerical stability, thus creating a set of weighted orthonormal dual Hahn polynomials. They are allowed to define a new type of discrete orthogonal moments. The discrete orthogonality of the proposed dual Hahn moments not only ensures the minimal information redundancy, but also eliminates the need for numerical approximations. The paper also discusses the computational aspects of dual Hahn moments, including the recurrence relation and symmetry properties. Experimental results show that the dual Hahn moments perform better than the Legendre moments, Tchebichef moments, and Krawtchouk moments in terms of image reconstruction capability in both noise-free and noisy conditions. The dual Hahn moment invariants are derived using a linear combination of geometric moments. An example of using the dual Hahn moment invariants as pattern features for a pattern classification application is given.
Complete list of metadatas

Cited literature [26 references]  Display  Hide  Download

https://www.hal.inserm.fr/inserm-00189813
Contributor : Lotfi Senhadji <>
Submitted on : Friday, November 23, 2007 - 4:00:12 PM
Last modification on : Friday, July 5, 2019 - 10:16:02 AM
Long-term archiving on: : Monday, April 12, 2010 - 3:13:34 AM

Identifiers

Collections

Citation

Hongqing Zhu, Huazhong Shu, Jian Zhou, Limin Luo, Jean-Louis Coatrieux. Image analysis by discrete orthogonal dual Hahn moments. Pattern Recognition Letters, Elsevier, 2007, 28 (13), pp.1688-1704. ⟨10.1016/j.patrec.2007.04.013⟩. ⟨inserm-00189813⟩

Share

Metrics

Record views

385

Files downloads

1038