Canny Sub-pixel Edge Detection Method Based on Threshold Segmentation and Markov Field Correction

Abstract

Markov field correction based on threshold segmentation Canny sub-pixel edge detection algorithm is of great significance for image position correction, accurate target segmentation and contour fitting. First, we adjust the brightness and contrast of the image to highlight the target area. Secondly, classical edge detection algorithms such as Sobel and Canny algorithms are used to extract the contour of the target image. However, we find that the performance of these algorithms will decline when there is noise interference. Therefore, in order to eliminate the side effects of noise, Perona-Malik (PM) model and Markov field correction method based on threshold segmentation are used to denoise the image. Then the above two algorithms are combined to extract the image contour. The experimental results show that the image contour extracted by Canny algorithm has high accuracy.