[1]赵小强,岳宗达.一种面向图像拼接的快速匹配算法[J].南京理工大学学报(自然科学版),2016,40(02):165.[doi:10.14177/j.cnki.32-1397n.2016.40.02.006]
　Zhao Xiaoqiang,Yue Zongda.Fast matching algorithm for image mosaic[J].Journal of Nanjing University of Science and Technology,2016,40(02):165.[doi:10.14177/j.cnki.32-1397n.2016.40.02.006]
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一种面向图像拼接的快速匹配算法
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《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

卷:
40卷
期数:
2016年02期
页码:
165
栏目:
出版日期:
2016-04-30

文章信息/Info

Title:
Fast matching algorithm for image mosaic
文章编号:
1005-9830(2016)02-0165-07
作者:
赵小强1; 2; 岳宗达1
1.兰州理工大学 电气工程与信息工程学院,甘肃 兰州 730050; 2.甘肃省工业过程先进控制实验室,甘肃 兰州 730050
Author(s):
Zhao Xiaoqiang1; 2; Yue Zongda1
1.College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China; 2.Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou 730050,China
关键词:
图像匹配;  尺度不变特征变换;  自适应非极大值抑制;  Radon变换;  随机抽样一致性
Keywords:
image matching;  scale invariant feature transform;  adaptive non-maxima suppression;  Radon transform;  random sample consistency
分类号:
TP751.1
DOI:
10.14177/j.cnki.32-1397n.2016.40.02.006
摘要:
针对图像拼接中尺度不变特征变换(Scale invariant feature transform,SIFT)算法的计算复杂度高、实时性差和误匹配等问题,提出了一种基于自适应非极大值抑制(Adaptive non-maxima suppression,ANMS)的Radon-SIFT方法。首先采用SIFT特征检测提取初始特征点,并用ANMS对初始特征点进行优选,得到分布均匀的特征点集; 在特征区域内做一系列直线,以这些直线上的Radon变换值作为特征描述符,以欧氏距离为度量准则进行特征匹配,然后采用随机抽样一致性(Random sample consistency,RANSAC)算法剔除误匹配点,从而提高了算法的正确匹配率和运算速率。仿真结果表明,该文算法具有较高的精度和较强的鲁棒性,且运算量少,实时性强。
Abstract:
Aiming at the problems of the large computation,the poor real-time and the mismatching of the scale invariant feature transform(SIFT)algorithm for image mosaic,a Radon-SIFT method based on the adaptive non-maxima suppression(ANMS)is proposed here.Firstly,this method uses feature detector of SIFT to extract initial feature points,and then the initial feature points are preferred by ANMS,so the feature point set of uniform distribution is obtained.Secondly,series of lines are made in the feature area.Image Radon transform integral values on the lines are adopted as feature vector descriptors and the features are matched by the measure criterion of the Euclidean distance.The Random sample consistency(RANSAC)algorithm is used to eliminate mismatching points and the computation speed and the correct matching rate are improved.Simulation results show that the proposed algorithm has the higher accuracy and robustness,and the amount of its arithmetic operation is reduced.

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备注/Memo

备注/Memo:
收稿日期:2015-09-07 修回日期:2015-12-07
基金项目:国家自然科学基金(51265032; 61263003); 甘肃省基础研究创新群体(1506RJIA031)
作者简介:赵小强(1969-),男,博士,教授,主要研究方向:生产调度建模与优化算法、故障诊断、图像处理,E-mail:xqzhao@lut.cn。
引文格式:赵小强,岳宗达.一种面向图像拼接的快速匹配算法[J].南京理工大学学报,2016,40(2):165-171.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2016-04-30