In order to realize the intelligent control of the micro knob, the key task is to obtain the accurate position and pose of the knob. Based on this, a new method of knob pose measurement combining edge detection and deep network is proposed. Firstly, to solve the problem of measurement error caused by image tilt, an improved Canny algorithm was proposed to extract the accurate edge and correct it by combining perspective transform. Secondly, the improved YOLO-V4 algorithm is used to achieve the precise segmentation of the knob. Finally, the improved Canny algorithm and bicubic spline interpolation were used to extract the high-precision knob groove sub-pixel contour, and the PCA algorithm was used to fit the contour rectangle and measure the position and pose. Experimental results show that the proposed improved Canny algorithm improves the accuracy of edge extraction and effectively reduces false edges. Compared with the YOLO-V4 knob detection algorithm, the average detection accuracy of the improved YOLO-V4 knob detection algorithm is improved by 2.92%, reaching 99.49%. The measurement accuracy of the center position and deflection angle of the knob grooves reaches 1.5pixel and 1.5° respectively, which can realize the high-precision measurement of the knob position and pose.