The comparison of canny and structured forests edge detection application in precision identification of pointer instrument

As an indispensable measuring instrument, the pointer instrument has been widely used in the fields of industrial production. While the manual instrument identification has problems of higher labor intensity, higher rate of misjudgment and lower production, we take advantage of computer vision to deal with the images of pointer instrument dials. Two algorithms are proposed for image edge detection: structured random forests edge detection and canny edge detection, Hough transform is used to recognize the straight lines of the pointer, then the automation of instrument identification can be realized. Our results show that the accuracy of the dials printed by the two methods can meet the production requirements.