Line-based matching for high-resolution images with robust for scale, rotation and illumination

SHAO Zhen-feng; CHEN Min

doi:10.3788/OPE.20132103.0790

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Line-based matching for high-resolution images with robust for scale, rotation and illumination

更新时间：2020-08-12

- Line-based matching for high-resolution images with robust for scale, rotation and illumination
- Optics and Precision Engineering Vol. 21, Issue 3, Pages: 790-798(2013)
- 作者机构：
  
  华中科技大学电子与信息工程系/光电国家实验室2. 武汉大学测绘遥感信息工程国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20132103.0790
  CLC： TP75
- Received：23 August 2012，
  
  Revised：18 October 2012，
  
  Published Online：20 March 2013，
  
  Published：15 March 2013
- 稿件说明：
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邵振峰陈敏. 尺度、旋转以及亮度稳健的高分辨率影像直线特征匹配[J]. 光学精密工程, 2013,21(3): 790-798

SHAO Zhen-feng CHEN Min. Line-based matching for high-resolution images with robust for scale, rotation and illumination[J]. Editorial Office of Optics and Precision Engineering, 2013,21(3): 790-798
邵振峰陈敏. 尺度、旋转以及亮度稳健的高分辨率影像直线特征匹配[J]. 光学精密工程, 2013,21(3): 790-798 DOI： 10.3788/OPE.20132103.0790.

SHAO Zhen-feng CHEN Min. Line-based matching for high-resolution images with robust for scale, rotation and illumination[J]. Editorial Office of Optics and Precision Engineering, 2013,21(3): 790-798 DOI： 10.3788/OPE.20132103.0790.

摘要

针对点特征匹配方法中特征的独特性不高，在弱纹理区域的影像匹配存在不足等问题，提出了一种尺度、旋转以及亮度稳健的高分辨率影像直线段特征匹配方法。首先，对待匹配的影像进行边缘检测和拟合，提取直线段特征；然后，将直线段特征分级，利用特征的方向关系匹配长直线段特征；最后，以同名长直线段特征对作为控制基础，以角度和距离作为量化特征，构造关系描述符，实现短直线段特征的匹配。实验结果表明，由于在同一幅影像中，每条特征直线段所在直线都有唯一对应的直线方程，特征的独特性很高，所以可以很好地避免误匹配，得到的正确匹配概率为90%以上，且均方根误差达到了亚像素级。该匹配方法在弱纹理区域比点特征匹配方法具有明显的优势，能够较好地满足应用需求。

Abstract

A line feature matching method for high-resolution images was proposed to improve the low significant level of a point feature and to overcome the matching shortage between weak texture images. Firstly

the edges of images were extracted and tracked to fit straight-lines. All straight-lines were classified into two groups: long-lines and short-lines. The long-lines were matched based on the direction relationship primarily. Then

the relationship-descriptors of short-lines were constructed using the angle and the Euclidean distance between the short-line and long correspondences. Finally

short-lines were matched according to the similarity of their relationship-descriptors. The experimental results demonstrate that the proposed line matching algorithm is robust for the scale

rotation and illumination. As all the lines have a corresponding linear equation in the same image

the image feature has higher significant level and can avoid the mismatching. The probability of correct matches of the algorithm exceeds 90% and its root mean square error has achieved sub-pixel level. The performance of the proposed algorithm is better than that of the point-based method

especially in weak texture areas.

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references

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