地貌测量中图像特征的匹配算法

王崴 1; 2; 李培林 2; 张宇红 3; 韩华亭 2; 杨鹏涛 1

您当前的位置：

首页 >

文章列表页 >

地貌测量中图像特征的匹配算法

专题研究 | 更新时间：2025-12-08

- 地貌测量中图像特征的匹配算法
- Image Feature Matching Algorithm Research on Topography Measurement
- 西安交通大学学报 2008年42卷第7期页码：870-874
- 作者机构：
  
  1. 西安交通大学机械制造系统工程国家重点实验室,西安,710049
  2. 空军工程大学导弹学院发射工程系, 713800, 陕西三原
- 作者简介：
- 基金信息：
  
  : 2007-12-03. 作者简介: 王崴(1974-),男,副教授. 基金项目: 国家自然科学基金资助项目(50505051)
- DOI：
  中图分类号： TP391.3
- 网络首发：2008-07-10，
  
  纸质出版：2008
- 稿件说明：
移动端阅览
王崴 1, 2, 李培林 2, 等. 地貌测量中图像特征的匹配算法[J]. 西安交通大学学报, 2008,42(7):870-874.

王崴 1, 2, 李培林 2, et al. Image Feature Matching Algorithm Research on Topography Measurement[J]. 2008, 42(7): 870-874.
王崴 1, 2, 李培林 2, 等. 地貌测量中图像特征的匹配算法[J]. 西安交通大学学报, 2008,42(7):870-874. DOI：

王崴 1, 2, 李培林 2, et al. Image Feature Matching Algorithm Research on Topography Measurement[J]. 2008, 42(7): 870-874. DOI：

摘要

针对地貌测量重构中的图像特征匹配问题

提出了一种新的图像特征匹配方法.通过对待匹配的资源和模板图像进行分区

并根据灰度相关值实现区域之间的匹配

在区域匹配的基础上再根据角点所属区域的对应关系进行角点特征匹配运算.在角点特征匹配过程中

利用去均值归一化相关法进行区域灰度相关运算

从而确定出初始匹配点对.为消除初始匹配角点对中的错误匹配点对

保证角点特征提取的准确性和可靠性

采用松弛迭代法、零交叉法以及最小平方中值法进行了错误匹配角点的滤除.实验结果表明

该算法可有效提高地貌图像特征匹配的精度和效率.

Abstract

To effectively realize the image feature matching for topography measurement and rebuilding

a new matching scheme is presented

where the topography resource image and model image matched are partitioned at first

and then the regions are matched according to the gray level correlation. Based on the region match

the corner feature match operation is processed following the relationship among the regions to which the corner points belong. During the corner feature match operation

the initial matching points are determined by region gray level correlation calculation with removing mean value normalization method. To eliminate the wrong matching points and assure the accuracy and reliability of corner detection

relaxation iteration algorithm

zero-crossing method and least squares escalator algorithms are adopted. The experiment results show the precision and accuracy of this algorithm for topography image feature match.

关键词

Keywords

references

YAN Ke, SUKTHANKAR R. PCA-SIFT: a more distinctive representation for local image descriptors[C]∥IEEE Conference on Computer Vision and Pattern Recognition. New York, USA: IEEE Computer Society Press, 2004: 506-503.

MILOLAJCZYK K, SCHMID C. A performance evaluation of local descriptors [J]. IEEE Trans: Pattern Analysis and Machine Intelligence, 2005, 27(10): 1615-1630.

LOWE D G. Object recognition from local scale-invariant features[C]∥International Conference on Computer Vision. Alamitors, CA, USA: IEEE Computer Society Press, 1999: 1150-1157.

MILOLAJCZYK K, SCHMID C. Scale affine invariant interest point detectors [J]. International Journal of Computer Vision, 2004, 60(1):63-86.

MAXIME L, LONG Quan. Robust dense matching using local and global geometric constraints[C]∥Proceedings of the 16th International Conference on Pattern Recognition. Alamitors, CA, USA: IEEE Computer Society Press, 2000: 968-972.

BEARDSLEY P, TORT P, ZISSERMA A. 3D model acquisition from extended image sequences[C]∥Proceedings of the 4th European Conference on Computer Vision. London, England: Springer-Verlag, 1996: 683-695.

PRITCH P, ZISSERMA A. Matching and reconstruction from widely separated views in 3d structure from multiple images of large-scale environments[C]∥Lecture Notes in Computer Science 1506. Freiburg, German: Springer-Verlag, 1998: 219-224.

PILU M. A direct method for stereo correspondence based on singular value decomposition[C]∥Proceedings of Computer Vision and Pattern Recognition. San Juan, Piscataway, NJ, USA: IEEE Computer Society Press, 1997: 445-453.

李峰,周源华.变形系数相关的最小二乘匹配算法[J].上海交通大学学报,1999,33(11):1391-1394.

LI Feng, ZHOU Yuanhua. Distortion parameter correlating least square matching algorithm[J]. Journal of Shanghai Jiaotong University, 1999, 33(11):1391-1394.

李峰,周源华.采用金字塔分解的最小二乘影像匹配算法[J].上海交通大学学报,1999,33(5):513-515.

LI Feng, ZHOU Yuanhua. Least square matching algorithm using pyramid decomposing[J]. Journal of Shanghai Jiaotong University, 1999, 33(5): 513-515.

LOWE D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2): 91-110.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

无序多视角点云的自主配准方法

张角凹坑气膜孔对双层壁气膜冷却特性的影响

混合电解槽阵列协同的风光耦合制氢系统双层多目标优化

语义区分和子图整合驱动的知识图谱表示学习方法

水蒸气掺混对氨裂解气旋流燃烧与排放特性的影响研究