Sub-Pixel Edge Detection Algorithm Based on Canny–Zernike Moment Method

Abstract

In order to solve the problems of low efficiency and long running time caused by the traditional Zernike moment method for convolution calculation of the whole image, this paper combines the canny detection algorithm with the Zernike moment method. First, the canny edge detection algorithm, which combined with the Otsu threshold method, is used to extract the pixel edge of the image. Then an improved Hough transform method is used to fit the geometric edge in the image. Based on this, the Zernike moment method is applied to realize sub-pixel positioning of images. The algorithm improves the deficiencies of direct sub-pixel detection, improving accuracy and reducing running time. To verify the effectiveness of the proposed algorithm, the algorithm is applied to the dimension measurement experiment of T-type guide way. The results clearly show that the algorithm is superior to the traditional algorithm in accuracy.