• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2010, Vol. 32 ›› Issue (8): 67-70.doi: 10.3969/j.issn.1007130X.2010.

• 论文 • 上一篇    下一篇

基于Hough变换的实验数据坏点剔除方法

陈苏1,林嘉宇2   

  1. (1.北京邮电大学电信工程学院,北京 100071;2.国防科学技术大学电子科学与工程学院,湖南 长沙 410073)
  • 收稿日期:2009-03-05 修回日期:2009-10-10 出版日期:2010-07-25 发布日期:2010-07-28
  • 基金资助:

    陈苏(1985),男,北京人,硕士生,研究方向为图像处理和模式识别;林嘉宇,博士,副教授,研究方向为非线性信号处理、信源编码、信源信道联合编码和通信中的信号处理等。

A Method of Experimental Defect Rejection Based on the Hough Transform

CHEN Su1,LIN Jiayu2   

  1. (1.School of Electronic and Telecommunications Engineering,Beijing University of Post and Telecommunications,Beijing 100876;〖JP〗2.School of Electronics Science and Engineering,National University of Defense Technology,Changsha 410073,China)
  • Received:2009-03-05 Revised:2009-10-10 Online:2010-07-25 Published:2010-07-28

摘要:

在实验测试中,除了获得包含误差的正常数据,实验员常常也可能观察到一些明显错误的点,我们称之为“坏点”。坏点的存在可能会严重影响实验最终结果的可靠性,所以在数据分析前,应该被处理掉。以往的常规坏点处理方法多为肉眼查看,手动排除。这种方法工作量大,并且判断依据不够明确,只靠“感觉”,另外,在接收到大量数据的时候,手动法无能为力。本文在使用计算机编程的基础上,应用Hough变换,提出了一种坏点剔除的新方法,可处理符合直线拟合特征的实验数据中的坏点;作为扩展应用,该方法也可以处理以下两种数据:可通过函数变换转化为符合线性分布的数据和Hough变换可处理的服从曲线分布的数据。仿真实验和实际应用表明,本方法具有较好的性能。

关键词: 实验数据拟合, 坏点剔除, Hough变换

Abstract:

In experimental tests, apart from obtaining the normal data with allowable errors, the experimenters usually get some unexpected wrong data called “defect marks”. Following the routine method of experimental data processing, the method of bad point exclusion based on automatic programming is seldom taken into consideration by experimenters. This article presents a new method based on the Hough transform to reject bad points. The method is fit for processing data with linear characteristics and can be extended to deal with the data that is possible to be translated into a linear form through functional transformations; curved lines, which can well be processed by the Hough transformation, can be its application too. Simulation experiments and practical applications  manifest that the method raised in this paper performs robustly.

Key words: experimental data fitting;defect rejection;Hough transform