Canny algorithm
2016-08-23
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In 1986, canny proposed Canny edge detection operator in his master's thesis of MIT [10]. Canny operator is a multi-stage optimization operator with filtering, enhancement and detection. It has good performance of edge detection. It has been more and more widely used. Canny examined the previous edge detection operators and their applications, and found that although the applications of these operators appear in different fields, they all have some common requirements: [3] (1) Good detection effect, that is to say, the error detection of the edge should be as low as possible: there must be false edges in the detection results where the edge of the image appears. In all systems that use edge detection for further research, its performance depends on the error of edge detection. (2) The location of the edge should be accurate: the marked edge should be close to the center of the real edge of the image. (3) Low response times to the same edge. That is to say, the probability of multiple responses generated by a single edge should be as low as possible, and the response of false edge should be suppressed as much as possible. These are the three principles proposed by Canny. He is the first person to put forward these three principles clearly and solve these three problems completely. He expressed the above principles with mathematical expressions, and then used optimization theory to get the optimal template of edge detection. The steps of Canny operator are as follows: (1) smooth the image with Gaussian filter. (2) The gradient amplitude and direction of the smoothed image are calculated. (3) Non maximum suppression is used to suppress the gradient amplitude. The process is to find out the local maximum points in the image gradient and set other non maximum points to zero to get the refined edge. (4) Edge detection and connection with double threshold algorithm & nbsp;
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