Construction of a complete set of orthogonal Fourier-Mellin moment invariants for pattern recognition applications

被引：40
|
作者：
Zhang, H. [1 ]
Shu, H. Z. [1 ]
Haigron, P. [2 ,3 ]
Li, B. S. [4 ]
Luo, L. M. [1 ]
机构：
[1] Southeast Univ, Lab Image Sci & Technol, Sch Engn & Comp Sci, Nanjing 210096, Peoples R China
[2] INSERM, U642, F-35042 Rennes, France
[3] Univ Rennes 1, Lab Traitement Signal & Image, F-35042 Rennes, France
[4] Shandong Canc Hosp, Dept Radiat Oncol, Jinan 250117, Peoples R China
来源：
IMAGE AND VISION COMPUTING | 2010年 / 28卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Orthogonal Fourier-Mellin moments; Completeness; Similarity invariants; Moment invariants; Pattern recognition; SCALE INVARIANTS; CHARACTER-RECOGNITION; IMAGE-RECONSTRUCTION; ZERNIKE; TRANSLATION;
D O I：
10.1016/j.imavis.2009.04.004
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The completeness property of a set of invariant descriptors is of fundamental importance from the theoretical as well as the practical points of view. In this paper, we propose a general approach to construct a complete set of orthogonal Fourier-Mellin moment (OFMM) invariants. By establishing a relationship between the OFMMs of the original image and those of the image having the same shape but distinct orientation and scale, a complete set of scale and rotation invariants is derived. The efficiency and the robustness to noise of the method for recognition tasks are shown by comparing it with some existing methods on several data sets. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：38 / 44
页数：7
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