Comprehensive Study of Continuous Orthogonal Moments-A Systematic Review

被引：15

作者：

Kaur, Parminder ^{[1
]}

Pannu, Husanbir Singh ^{[1
]}

Malhi, Avleen Kaur ^{[1
]}

机构：

[1] Thapar Inst Engn & Technol, CSED, POB 32,Bhadson Rd, Patiala 147004, Punjab, India

来源：

ACM COMPUTING SURVEYS | 2019年 / 52卷 / 04期

关键词：

Jacobi Fourier moments; Pseudo-Jacobi Fourier moments; Zernike moments; Legendre moments; Gegenbauer moments; Chebyshev Fourier moments; Orthogonal Fourier Mellin moments; Laguerre moments; Gaussian-Hermite moments; continuous Hahn moments; Bessel Fourier moments; Radial Harmonic Fourier moments; JACOBI-FOURIER MOMENTS; INVARIANT IMAGE RECOGNITION; GAUSSIAN-HERMITE MOMENTS; ZERNIKE MOMENTS; CHARACTER-RECOGNITION; PATTERN-RECOGNITION; LEGENDRE MOMENTS; SCALE INVARIANTS; COMPUTATION; WATERMARKING;

D O I：

10.1145/3331167

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Orthogonal moments provide an efficient mathematical framework for computer vision, image analysis, and pattern recognition. They are derived from the polynomials that are relatively perpendicular to each other. Orthogonal moments are more efficient than non-orthogonal moments for image representation with minimum attribute redundancy, robustness to noise, invariance to rotation, translation, and scaling. Orthogonal moments can be both continuous and discrete. Prominent continuous moments are Zernike, Pseudo-Zernike, Legendre, and Gaussian-Hermite. This article provides a comprehensive and comparative review for continuous orthogonal moments along with their applications.

引用

页数：30

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