muneeswaris1991 / color-edge-detection Goto Github PK

A typical edge might for instance be the border between a block of red color and a block of yellow. In contrast a line (as can be extracted by a ridge detector) can be a small number of pixels of a different color on an otherwise unchanging background. For a line, there may therefore usually be one edge on each side of the line. Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. The Process of Canny edge detection algorithm can be broken down to 5 different steps: 1 Apply Gaussian filter to smooth the image in order to remove the noise. 2 Find the intensity gradients of the image. 3 Apply non-maximum suppression to get rid of spurious response to edge detection. 4 Apply double threshold to determine potential edges. The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. It was developed by John F. Canny in 1986.