华南理工大学学报(自然科学版) ›› 2016, Vol. 44 ›› Issue (5): 117-122.doi: 10.3969/j.issn.1000-565X.2016.05.018

• 计算机科学与技术 • 上一篇    下一篇

基于改进空间矩算法的光纤纤芯轮廓特征点快速提取

陈忠 周德文 张宪民   

  1. 华南理工大学 机械与汽车工程学院,广东 广州 510640
  • 收稿日期:2015-07-20 修回日期:2015-11-28 出版日期:2016-05-25 发布日期:2016-04-12
  • 通信作者: 陈忠(1968-),男,博士,副教授,主要从事机器视觉及其应用、精密测量和故障诊断研究. E-mail:mezhchen@scut.edu.cn
  • 作者简介:陈忠(1968-),男,博士,副教授,主要从事机器视觉及其应用、精密测量和故障诊断研究.
  • 基金资助:
    国家公派出国留学基金资助项目(201506155012);广东省自然科学基金研究团队项目(S2013030013355)

Fast Extraction of Feature Points for Contours of Optical Fiber Cores Based on Improved Spatial Moment Algorithm

CHEN Zhong ZHOU De-wen ZHANG Xian-min   

  1. School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2015-07-20 Revised:2015-11-28 Online:2016-05-25 Published:2016-04-12
  • Contact: 陈忠(1968-),男,博士,副教授,主要从事机器视觉及其应用、精密测量和故障诊断研究. E-mail:mezhchen@scut.edu.cn
  • About author:陈忠(1968-),男,博士,副教授,主要从事机器视觉及其应用、精密测量和故障诊断研究.
  • Supported by:
    Supported by the State Scholarship Fund of China(201506155012) and the Research Team Project of the Natu- ral Science Foundation of Guangdong Province(S2013030013355)

摘要: 为了提高基于视觉的光纤精密对接的特征点提取速度和定位精度,提出了一种基于改进空间矩算法的光纤纤芯轮廓特征点亚像素快速提取算法. 该算法首先对光纤纤芯的初始位置进行快速搜索,进而对纤芯和光纤端面进行边缘追踪,提取出纤芯的边缘;然后采用改进空间矩算法得到边缘的亚像素位置,并对提取到的纤芯边缘点和端面边缘点进行直线拟合,求取光纤中轴线及端面直线方程. 实验结果表明,文中提出的光纤纤芯轮廓特征点提取算法相对于传统方法具有提取速度快、抗噪性好和定位精度高的特点,能满足实时精密对接光纤的要求.

关键词: 计算机视觉, 特征提取, 一维空间矩, 光纤

Abstract: In order to improve the speed and accuracy of vision-based feature point extraction for optical fibers in their precision alignment process,a rapid extraction algorithm of subpixel feature points for contours of optical fiber cores is proposed on the basis of an improved spatial moment algorithm.In the proposed algorithm,firstly,the initial position of optical fibers is quickly searched,and the pixel-level edges of fiber cores are extracted via tracking the cores and their end faces.Then,subpixel edges are located by means of an improved spatial moment method,and linear equations of the axle and the edges are derived after a linear fitting on the extracted subpixel edges.Experimental results show that the proposed extraction algorithm runs more rapidly and possesses higher precision and stronger noise robustness than the traditional method,and that it meets the requirements of real-time precision alignment of optical fibers.

Key words: computer vision, feature extraction, one-dimension spatial moment, optical fiber

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