华南理工大学学报(自然科学版) ›› 2008, Vol. 36 ›› Issue (8): 37-40.

• 电子、通信与自动控制 • 上一篇    下一篇

RSTC不变矩图像特征点匹配新方法

邵泽明 朱剑英   

  1. 南京航空航天大学 江苏省精密与微细制造技术重点实验室, 江苏 南京 210016
  • 收稿日期:2007-07-17 修回日期:2007-10-25 出版日期:2008-08-25 发布日期:2008-08-25
  • 通信作者: 邵泽明(1975-),男,博士生,主要从事图像处理、机器视觉研究. E-mail:nj_szm@sohu.com
  • 作者简介:邵泽明(1975-),男,博士生,主要从事图像处理、机器视觉研究.
  • 基金资助:

    国家自然科学基金资助项目(50275078)

New Matching Method of Image Features Based on Moment Invariants of RSTC

Shao Ze-ming  Zhu Jian-ying   

  1. Jiangsu Key Laboratory of Precision and Micro-Manufacturing Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
  • Received:2007-07-17 Revised:2007-10-25 Online:2008-08-25 Published:2008-08-25
  • Contact: 邵泽明(1975-),男,博士生,主要从事图像处理、机器视觉研究. E-mail:nj_szm@sohu.com
  • About author:邵泽明(1975-),男,博士生,主要从事图像处理、机器视觉研究.
  • Supported by:

    国家自然科学基金资助项目(50275078)

摘要: 针对图像特征点的匹配中单纯依靠灰度度量会出现多峰值以及匹配不可靠、不准确的问题,提出了一种新的基于RSTC不变矩的匹配方法.该方法首先用改进的SUSAN算法找到角点,然后构造一种新的RSTC不变矩来描述角点特征,并用RSTC不变特征量作为匹配相似度的度量,再结合RANSAC鲁棒估计以及外极线约束进行引导匹配.对实际图像的实验表明,该方法可以获得比较好的匹配结果,消除了野值匹配所导致的长线条,并且精度比灰度匹配方法提高了6%以上.

关键词: 图像匹配, 特征提取, SUSAN算法, 角点检测, 不变矩, 鲁棒估计, 外极线

Abstract:

In the matching of image features, a great deal of peaks may occur and unreliable and inaccurate matching results are obtained due to the gray measure. In order to solve these problems, a new matching method of image features is proposed based on the moment invariants of rotation, scale, translation and contrast (RSTC). In the new matching method, an improved SUSAN algorithm is employed to detect the comers. Then, a new moment invariant of RSTC is constructed to describe the corner features and to measure the similarity of corner matching. Moreover, a guided matching with RANSAC robust estimation and epipolar line constraint is performed. Experimental results of actual images show that the proposed method eliminates the long lines caused by wrong feature matching and is of excellent matching effectiveness, and that it improves the matching precision by more than 6% as compared with the gray matching method.

Key words: image matching, feature extraction, SUSAN algorithm, comer detection, moment invariant, robust estimation, epipolar line