|本期目录/Table of Contents|

[1]单宝明,胥喜龙.一种结合ORB算法的SIFT图像配准算法[J].工业仪表与自动化装置,2017,(02):27-30.
　SHAN Baoming,XU Xilong.A SIFT image registration algorithm combined with ORB algorithm[J].Industrial Instrumentation & Automation,2017,(02):27-30.
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一种结合ORB算法的SIFT图像配准算法

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2017年02期
页码:
27-30
栏目:
出版日期:
2017-04-15

文章信息/Info

Title:
A SIFT image registration algorithm combined with ORB algorithm
文章编号:
1000-0682(2017)02-0000-00
作者:
单宝明; 胥喜龙
（青岛科技大学 自动化与电子工程学院，山东 青岛 266042）
Author(s):
SHAN Baoming;  XU Xilong
(College of Automation & Electronic Engineering, Qingdao University of Science &Technology,Shandong Qingdao 266042,China )
关键词:
SIFT; 特征提取; 特征匹配; ORB算法
Keywords:
SIFT;  Feature extraction;  Feature matching;  ORBalgorithm
分类号:
TP391.41
DOI:
-
文献标志码:
A
摘要:
在基于SIFT算法的图像配准过程当中有两个重要的环节：特征提取和特征匹配。针对算法在特征提取时存在的计算大、复杂度高、速度慢等问题，该文提出了结合ORB算法的思想，对SIFT算法进行特征提取的优化，从而实现快速的提取图像的局部特征。在特征匹配阶段采用K最近邻的BBF搜索策略并结合RANSAC算法进行提纯，消除误配点。实验结果表明，改进后的算法降低了配准时间并且提高了配准的精度，适用于一些对实时性要求较高的场合。
Abstract:
In the process of image registration based on SIFT algorithm, there are two important steps: feature extraction and feature matching.In view of the problem of large computation, high complexity and slow speed in feature extraction,this paper puts forward the idea of combining ORB algorithm, the SIFT algorithm to optimize the feature extraction, so as to achieve the rapid extraction of local features of the image.In the feature matching stage, the BBF search strategy of K nearest neighbor is adopted and the RANSAC algorithm is used to purify and eliminate the error matching point.The experimental results show that the improved algorithm can reduce the registration time and improve the accuracy of registration, which is suitable for the occasions with high real-time requirements.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2016-07-22
作者简介：单宝明（1974），男，山东东营人，硕士，副教授，硕士生导师，研究方向为嵌入式系统设计，智能控制技术。
更新日期/Last Update: 1900-01-01