Research on Edge Detection Algorithm of Railroad Fastener Image based on FPGA FPGA implementation of an efficient railroad fastener image edge detection algorithm

Most of the railroad fastener images have the problems of low contrast, complex image noise and difficult to recognize edge details.For these difficult problems, this paper improves the traditional Canny algorithm by using a hybrid filter composed of adaptive median filter and Gaussian filter to preprocess the image; improves the Sobel operator by using 5*5 eight-direction templates instead of the traditional 3*3 four-direction templates, and expands the computational direction of the non-maximum value suppression module to eight directions.The experimental results show that the improved algorithm has better image edge detection performance on FPGA, lower resource utilization and faster image processing.