摘要
针对气泡水平仪的自动标定问题,对机器视觉领域中的边缘提取算法、最小二乘法、轮廓跟踪算法等方面进行了研究。提出了一种基于Canny边缘检测和加权最小二乘法的气泡水平仪实时自动检测方法,以提高检测气泡水平仪的准确度和效率。引入了Canny边缘提取算法对工业摄像机所拍摄的水准柱侧面图像进行处理,以得到参考线和气泡的边缘信息。引入了一种自适应选取Canny边缘提取算法的阈值的方法,以克服工业现场光照变化的影响。同时针对本应用场合,采用了加权最小二乘法对左右平行参考线进行拟合,并结合二分搜索算法对水平尺上的气泡位置进行了搜索,从而实现了气泡水平仪的高准确度实时检测。研究结果表明,该方法能够准确、快速地对气泡进行定位,能够较好地适应光照变化。
Aiming at the automatic calibration problem of the bubble level,the edge detection algorithm,the least square method and the contour tracking algorithm in the field of machine vision were studied. A real-time automatic detection method for the level bar based on Canny edge detection and weighted least square method was proposed to improve the accuracy and efficiency of the bubble detection. The Canny edge extraction algorithm for image pre-processing was introduced to deal with the image of the level column taken by the industrial camera to get the edge information of the reference lines and the bubble. The thresholds of Canny edge extraction algorithm was set adaptively to reduce the effects of changes in the light field on detection accuracy. The weighted least squares was employed to model the parallel reference lines and the binary search algorithm was used to search the bubble position,so as to achieve high-accuracy detection of the level bar. The results indicate that the proposed method can accurately and quickly locate the bubble,and can well adapt to the changes of the light.
作者
盛伟
WANG Qing-guo
朱善安
SHENG Wei WANG Qing-guo ZHU Shan-an(College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China Institute of Intelligent Systems, School of Electrical Engineering, Johannesburg 2000, South Africa)
出处
《机电工程》
CAS
2016年第10期1182-1187,共6页
Journal of Mechanical & Electrical Engineering
