Improvement of canny algorithm based on pavement edge detection

In this paper we introduce an improved Canny edge detection algorithm and an edge preservation filtering procedure for pavement edge detection applications. Data of pavement images were randomly selected to test this algorithm. There are some problems of Canny operator, unable to detect the weak edge and distinguish the grayscale with little change, the detected edge uncontinuous. Based on these defects, the paper mainly uses the Mallat wavelet transform to reinforce the weak edge of input images, quadratic optimization of genetic algorithm to get a proper threshold in self-adapting standard during Canny algorithm steps. With the base of Canny operator and the improvement, the paper builds a new model, which satisfies the need of pavement edge detection real-time. Computer simulations show that the improved algorithm can make up for the disadvantages of Canny algorithm, detect edges of pavement images effectively, and is a less time-consuming process. Particularly, it has been shown that the presented algorithm can not only eliminate noises effectively but also protect unclear edges.