Image selection based on Grayscale features in robotic welding

In robotic welding seam tracking based on visual information has been studied in the recent years. However, it is difficult to ensure the quality of images obtained in the welding process because it is easily affected by spattering, fuming and electromagnetic noise. The paper introduces a method to select useful images before further processing. Experimental tests are conducted to verify its accuracy