Research on Improved Canny Edge Detection Algorithm
Aiming at the poor noise robustness of traditional Canny algorithm and the defect of false edge or edge loss,an edge detection algorithm using statistical algorithm for filtering denoising and using genetic algorithm to determine the optimal high and low threshold of image segmentation is proposed.Firstly,statistical filtering uses mean and variance to denoise,avoiding the problem of Gaussian denoising susceptible to interference in the traditional Canny algorithm,and ensuring the integrity of image edge information.Secondly,this article uses the genetic algorithm,design the crossover operator and genetic operator to modify the evolution of the population,and determine the optimal height threshold of the image edge connection to make the threshold more accurate.Finally,using MATLAB software to simulate,the results show that the improved Canny edge detection algorithm can further improve the anti-noise ability and robustness,and the edge location is more accurate.
Ruiyuan Liu Jian Mao
Shanghai University of Engineering Science,School Of Mechanical and Automotive Engineering,China
国际会议
上海
英文
1-4
2018-10-12（万方平台首次上网日期，不代表论文的发表时间）