vanditg / canny-s-edge-detection-with-reduced-noise-and-gaussian-blurred-effects Goto Github PK

Canny Edge Detection is a popular edge detection algorithm. It is a multi-stage algorithm. Since edge detection is susceptible to noise in the image, first step is to remove the noise in the image with a 5x5 Gaussian filter. Smoothed image is then filtered with a Sobel kernel in both horizontal and vertical direction to get first derivative in horizontal direction and vertical direction. After getting gradient magnitude and direction, a full scan of image is done to remove any unwanted pixels which may not constitute the edge. For this, at every pixel, pixel is checked if it is a local maximum in its neighborhood in the direction of gradient. we need two threshold values, minVal and maxVal. Any edges with intensity gradient more than maxVal are sure to be edges and those below minVal are sure to be non-edges, so discarded. Those who lie between these two thresholds are classified edges or non-edges based on their connectivity. If they are connected to "sure-edge" pixels, they are considered to be part of edges. Otherwise, they are also discarded.

License: The Unlicense