The phenomenon of burring is common in the manufacturing of metal parts. This phenomenon directly influences the assembly accuracy and service performance of the mechanical parts. In this work, we propose a vision?based method for two?dimensional planar workpiece. The proposed technique has the ability to recognize burr contour and generate the coordinate sequence in real?time along x and y directions. The robotic deburring efficiency is improved based on the quantitative information of the burr size. First, by utilizing the local deformable template matching algorithm, we match the standard workpiece contour with the workpiece contour to be processed and compute the corresponding pixels distance between the two contours. Second, we set the distance thresholds in order to divide the burr contours into different levels. We extract the coordinates of the burr contours and map them to the standard workpiece contour. As a result, the closed?loop robotic deburring path sequence is generated. Finally, on the basis of the quantitative information of burr size, we adjust the deburring speed in real?time during the deburring process. The experiments performed in this work show that the deburring time of the proposed method is reduced by 15.45％, as compared with the conventional off?line programming deburring methods. Therefore, for industrial mass production, the deburring efficiency is greatly improved.