基于数学形态学的气泡水平尺自动检测系统研究

针对气泡水平尺的自动检测问题,对机器视觉领域的边缘提取、轮廓跟踪等算法进行了研究,提出了一种基于数学形态学与轮廓跟踪的气泡水平尺自动检测方法。引入了快速中值滤波算法和多线程工具对工业相机拍摄的水平尺气泡图像进行了滤波处理,以提高中值滤波算法的运算效率,使用了模糊最小化形态学梯度对气泡图像进行处理,以得到气泡的边缘信息。同时针对该应用场合,分析了气泡边缘图像的灰度剖面特性得到左、右平行参考线的位置,结合目标邻域点法搜索气泡端点来对气泡位置进行了搜索,得到了气泡偏移距离,从而实现了高效率高准确度的气泡水平尺偏移实时检测。研究结果表明,该方法在保证结果准确的同时,能够极大提高计算速度,并且计算结果能极好地适应光照变化。

Automatic level bar inspection system based on mathematical morphology

Aiming at the automatic inspection of the level bar,the edge detecting and contour tracking algorithm in the field of machine vision were studied,and an automatic detection method for the lever bar based on mathematical morphology and contour tracking was proposed.In order to improve the efficiency of the median filter algorithm,a fast median filter algorithm and multithreading tool were used to deal with the image of the bubble in the level bar taken by the industrial camera.In order to get the edge information of the bubble,the fuzzy minimization morphological gradient was introduced to deal with the image of the bubble.Aiming at this application,grayscale profile of the image was analyzed toposition theparallel reference lines,and the target neighborhood point method is used to search the position of bubble around vertices,and calculate the deviation of the bubble,so as to achieve high-efficiency and high-accuracy deviation detection of the level bar.The result indicates that the proposed method can greatly improve the calculating speed while ensuring accurate results at the same time,and can well adapt to the light changes.