Recognition of circular workpiece in complex environment

With the development of science and technology, Using computer vision technology to detect and identify products has become a common application. As a common geometric figure in industrial production, circle often needs to be detected and recognized. In this paper, in order to solve the problem of the identification of the round workpiece in the complex environment, it is studied. Traditional Hough algorithm transforms image from original image space to parameter space, In the parameter space, we use some parameter form which most boundary points satisfy as the description of the curve in the image. industrial production environment is complex, Even if we try to eliminate noise or improve Hough algorithm, Still can't improve its recognition rate. For this reason, this paper proposes a method combining YOLOv3 deep learning system with Hough algorithm, which greatly improves the recognition rate of circular workpiece in complex industrial environment.