Fast algorithm of subpixel edge detection based on Zernike moments

The traditional Zernike moment-based method is often used for subpixel-level edge detection, but the algorithm still requires manual tuning on selecting threshold, not only inefficient, but also leads to the wrong detection of the edge and affecting the measurement accuracy. In order to overcome this weakness, this paper combines original algorithm with Otsu adaptive threshold algorithm and a new fast algorithm for edge detection is proposed. This fast algorithm can directly obtain the optimal step gray threshold and detect the edge. The detection time is significantly shortened while ensuring the detection results. This algorithm also calculates the error caused by edge model. Experimental results show that the improved algorithm can detect the image edge more effectively and the subpixel location is more accurate after compensating, the detection results are satisfied.