东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2007, Vol. 28 ›› Issue (9): 1270-1273.DOI: -

• 论著 • 上一篇    下一篇

采用最小均方误差筛选参数的Hough变换及应用

张祥德;王琪;黄亚平;曹宇;   

  1. 东北大学理学院;东北大学理学院;东北大学理学院;东北大学理学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2007-09-15 发布日期:2013-06-24
  • 通讯作者: Zhang, X.-D.
  • 作者简介:-
  • 基金资助:
    辽宁省自然科学基金资助项目(20042019);;

Hough transform with parameters chosen by LMSE method

Zhang, Xiang-De (1); Wang, Qi (1); Huang, Ya-Ping (1); Cao, Yu (1)   

  1. (1) School of Sciences, Northeastern University, Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2007-09-15 Published:2013-06-24
  • Contact: Zhang, X.-D.
  • About author:-
  • Supported by:
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摘要： 为了在含有大量噪声的图像中精确地检测形状,提出了采用最小均方误差筛选参数的Hough变换方法:首先采用Hough变换投票得到参数空间上的投票值,然后初步筛选出所有投票值大于投票阈值的参数,再分别计算这些参数对应图像在边界图像中的均方误差,最后选择其中均方误差最小的一组参数作为最后的检测结果.将该方法与取最大投票值的Hough变换分别应用于虹膜外边缘定位并相互比较,实验结果表明,该方法抗噪声能力更强,适用范围更大,得到的结果更加合理.

关键词: 最小均方误差, Hough变换, 参数筛选, 虹膜定位

Abstract: To detect a figure accurately in an image with great background noise, an improved Hough transform with parameters screened by least mean square error (LMSE) method is proposed as follows. First, Hough transform is introduced to obtain the total number of votes in parametric space, and the parameters of which the vote is greater than the threshold value for voting are all screened out preliminarily. Then, the mean square errors of image edges are separately calculated corresponding to these parameters, and a set of parameters with LMSE is chosen as the final result of such detection. The approach proposed is compared with the Hough transform with fetching the maximum votes by applying them separately to the localization of the outer iris limbus. Experimental results showed that the approach proposed can offer more reasonable findings with higher resistance to noise and wider range of applications.

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