改进的SIFT特征提取和匹配算法

曾峦; 王元钦; 谭久彬

doi:10.3788/OPE.20111906.1391

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改进的SIFT特征提取和匹配算法

信息科学 | 更新时间：2020-08-12

- 改进的SIFT特征提取和匹配算法
- Improved algorithm for SIFT feature extraction and matching
- 光学精密工程 2011年19卷第6期页码：1391-1397
- 作者机构：
  
  1. 哈尔滨工业大学超精密光电仪器工程研究所,黑龙江哈尔滨,150001
  2. 装备指挥技术学院北京,101416
- 作者简介：
- 基金信息：
  
  总装备部试验技术研究项目(No.2009SY4110005)()
- DOI：10.3788/OPE.20111906.1391
  中图分类号： TP391.41
- 收稿日期：2010-12-29，
  
  修回日期：2011-01-25，
  
  网络出版日期：2011-06-25，
  
  纸质出版日期：2011-06-25
- 稿件说明：
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曾峦, 王元钦, 谭久彬. 改进的SIFT特征提取和匹配算法[J]. 光学精密工程, 2011,19(6): 1391-1397

ZENG Luan, WANG Yuan-qin, TAN Jiu-bin. Improved algorithm for SIFT feature extraction and matching[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1391-1397
曾峦, 王元钦, 谭久彬. 改进的SIFT特征提取和匹配算法[J]. 光学精密工程, 2011,19(6): 1391-1397 DOI： 10.3788/OPE.20111906.1391.

ZENG Luan, WANG Yuan-qin, TAN Jiu-bin. Improved algorithm for SIFT feature extraction and matching[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1391-1397 DOI： 10.3788/OPE.20111906.1391.

摘要

针对月球影像和尺度不变特征变换(SIFT)算法的特点

在改进SIFT特征提取算法的基础上

提出了一种稳健的图像自动匹配策略。首先

自动调整SIFT算法中的对比度控制系数

提高关键点提取的均衡性;然后

用SIFT描述向量之间的欧氏距离最小值与次小值的比值作为阈值

进行粗匹配

并利用匹配对主方向角度差直方图剔除部分伪匹配;最后

自动计算随机采样次数、误差容忍度等参数

使用改进的随机选取一致性(RANSAC)方法确定透视变换模型初始参数

并用该模型和误差容忍度对匹配集合中的匹配对进行校验

选取出正确的匹配对。实验结果表明

在图像有一定程度的视点、光照、旋转、比例、模糊和对比度变化等情形下

该算法稳定、可靠。该方法能有效解决图像匹配门限的选择问题

真正实现了无人工干预的自动匹配。

Abstract

A robust automated image matching strategy based on an improved SIFT feature extraction algorithm was proposed according to the characteristics of SIFT algorithm and lunar images. Firstly

the extraction equilibrium of key points was improved by automatically adjusting the coefficient of controlling contrast in the SIFT algorithm.Then

the coarse matching was carried out by using the ratio of the minimum and the second minimum Euclidean distance between the description vectors of SIFT as a threshold and the part incorrect matching of the coarse matching set was removed by principal direction angle difference histogram of matches. Finally

the initial parameters of perspective transformation model were determined by using modified RANSAC method

automatically calculated random sampling numbers

and parameters of error tolerance. Moreover

the model and the error tolerance were used to calibrate the matching pairs in the matching set and to select the correct matching pairs. The experimental results prove that the proposed method is stable and reliable under some variations for view points

illumination

rotation

scale and out of focus and it can select the matching threshold of images automatically without manual intervention.

关键词

Keywords

references

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