Automatic object and image alignment using Fourier Descriptors

被引：20
|
作者：
Duan, Weisheng [2 ]
Kuester, Falko [1 ]
Gaudiot, Jean-Luc [3 ]
Hammami, Omar [4 ]
机构：
[1] Univ Calif San Diego, Dept Struct Engn, La Jolla, CA 92093 USA
[2] Ion Beam Applicat SA, B-1348 Louvain, Belgium
[3] Univ Calif Irvine, Dept Elect Engn & Comp Sci, Irvine, CA 92697 USA
[4] Ecole Natl Super Tech Avancees, F-75739 Paris 15, France
来源：
IMAGE AND VISION COMPUTING | 2008年 / 26卷 / 09期
基金：
美国国家科学基金会;
关键词：
image alignment; edge detection; Fourier Descriptors; correspondence; transformation; iterative closest point;
D O I：
10.1016/j.imavis.2008.01.009
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a new edge-based technique for image alignment, combining Fourier Descriptors (FD) and the Iterative Closest Point (ICP) computation into an accurate and robust processing pipeline. Once edges are identified in the reference and target images, Fourier Descriptors are used to simultaneously determine edge correspondence and estimate the transformation parameters. Subsequently, an ICP computation is applied to further improve the alignment results. Using Fourier Descriptors in combination with a reliable distance matrix, corresponding edge pairs can be reliably detected for all identified edges. (C) 2008 Published by Elsevier B.V.
引用
收藏
页码：1196 / 1206
页数：11
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