摘要
针对井下胶带运输机胶带跑偏的现象,提出了一种基于视觉计算的监测方法。首先对井下复杂环境下的视频图像进行图像滤波和边缘增强;然后采用Canny算子进行边缘检测,得到视频图像的边缘二值图像;其次根据胶带边缘直线特征采用Hough变换检测胶带的边缘,并设置感兴趣区域,这加快了图像的处理速度和可靠性;再次对胶带边缘直线的断裂现象,采用最小二乘拟合将断裂的直线段合并成一条完整的直线;最后根据拟合到的直线斜率值和直线与图像坐标系中x轴的交点值监测胶带的跑偏。
In this article, it presents an monitoring method based on visual computing for coal belt conveyor deviation problem. Video image in complex environment of underground mine is preprocessing image bilateral filtering and sharpening edge, the resultant image is using for obtaining the binary image with Canny operator. To set ROI （region of interest） of the binary image, Hough transform is applied for ROI to identify feature lines of the coal belt conveyor edge, the feature line segments are combined into a complete line by using Least Square. The algorithm is capable of monitoring deviation of the coal belt conveyor on the basis of the slope and intercept at the horizontal axis of the combined line.
出处
《煤矿安全》
CAS
北大核心
2014年第5期118-121,共4页
Safety in Coal Mines
基金
国家自然科学基金资助项目(U1261114)
