Features Image Matchingof SUＲF and ＲANSAC

WANG Wei-bing; BAI Xiao-ling; XU Qian

doi:10.15938/j.jhust.2018.01.021

Chinese

您当前的位置：

首页 >

文章列表页 >

Features Image Matchingof SUＲF and ＲANSAC

更新时间：2026-08-31

- Features Image Matchingof SUＲF and ＲANSAC
- Vol. 23, Issue 1, Pages: 117-121(2018)
- 作者机构：
  
  1. 哈尔滨理工大学计算机科学与技术学院,黑龙江,哈尔滨,150080
  2. 黑龙江电力有限公司哈尔滨供电公司,黑龙江,哈尔滨,150000
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2018.01.021
  CLC： TP391.4
- Published：2018
- 稿件说明：
移动端阅览
WANG Wei-bing, BAI Xiao-ling, XU Qian. Features Image Matchingof SUＲF and ＲANSAC[J]. 2018, 23(1): 117-121.
DOI：

WANG Wei-bing, BAI Xiao-ling, XU Qian. Features Image Matchingof SUＲF and ＲANSAC[J]. 2018, 23(1): 117-121. DOI： 10.15938/j.jhust.2018.01.021.

摘要

针对图像匹配过程中存在匹配运行时间长、匹配正确率低的问题，采用随机采样一致性( random sample consensus，ＲANSAC) 算法优化加速鲁棒特征( speed up robust features，SUＲF) 的方法，提出一种适应性强的优化匹配算法。首先使用SUＲF 算子进行特征检测和特征描述，再使用邻近算法对特征点进行预匹配，最后使用随机采样一致性( ＲANSAC) 算法优化匹配结果。在相同的实验环境中通过对尺度不变特征变换( scale invariant feature transform，SIFT) 算法、SUＲF 算法和提出的优化算法进行比较，优化算法较SIFT 算法和SUＲF 算法分别减少匹配点对数38 对和18对，剔除了误匹配点，提高了匹配正确率并减少了算法的运行时间。

Abstract

Aiming at the problem of long running time and low matching accuracy in image matching process，random sample consensus ( ＲANSAC) algorithm is used to optimize the speed-up of robust features ( SUＲF)optimization algorithm. As a result，an adaptable algorithm is proposed to optimize image matching. Firstly，theSUＲF operator is used for feature detection and feature description. Then the neighbor algorithm is used to prematchthe feature points. Finally，the random sampling consistency ( ＲANSAC) algorithm is used to optimize thematching results. The scale invariant feature transform ( SIFT) algorithm，SUＲF algorithm，and the proposedoptimization algorithm are compared in the same experimental environment. Compared with the SIFT algorithm andthe SUＲF algorithm，the optimization algorithm reduces the number of matching point pairs to 38 and 18 pairs，excluding mismatched points，improving the matching accuracy，and reducing the running time of the algorithm.

关键词

Keywords

references

Views

1064

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Ship Noises Classification Based on Hilbert-Huang Transform

一种求解二重积分的差分进化算法

基于Linux的进程间通信性能问题研究

无线通信自动校准系统设计

基于LCC谐振电路阻抗匹配的光伏发电最大功率点跟踪

Related Author

LI Xin-xin

NING Gui-ying

ZHOU Yong-quan

HAN Jian-hui

WANG Ze-feng

WANG Kai

LI Zhi

LI Ming-zhao

Related Institution

The 54th Research Institute of CETC

Lushan College,Guangxi University of Technology

College of Math and Computer Science,Guangxi University for Nationalities

School of Computer Science and Technology, Harbin University of Science and Technology

Institute of Metrology in Communications and Electronics,Shenzhen Academy of Metrology and Quality Inspectin

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰