Deviation Monitoring of Coal Belt Conveyor Based on Visual Computing

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.