Introduction - If you have any usage issues, please Google them yourself
Classical edge detection methods such as: Roberts, Sobel, Prewitt, Kirsch, Laplace and other algorithms, the basic are the original image pixel neighborhood structure of edge detection operator, for the first-order differential or second-order differential operator, obtained maximum gradient or second derivative of the zero-crossing point, and finally select the appropriate threshold boundary extraction. Since the algorithm involves computing the gradient, so there are sensitive to noise, such as the shortcomings of the calculation volume. In practice, SUSAN algorithm found only on the surrounding pixels based on comparison of the gray does not involve computing the gradient, so the strong anti-noise, computing the amount is relatively small, experimental proof of the algorithm is very suitable for images with noise edge detection.