1CannyEdgeDetectionTutorial

1CannyEdgeDetectionTutorial - Canny Edge Detection Tutorial...

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1 of 3 7/22/2009 10:13 PM Canny Edge Detection Tutorial Author: Bill Green (2002) HOME EMAIL This tutorial assumes the reader: (1) Knows how to develop source code to read raster data (2) Has already read my Sobel edge detection tutorial This tutorial will teach you how to: (1) Implement the Canny edge detection algorithm. INTRODUCTION Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Edges in images are areas with strong intensity contrasts – a jump in intensity from one pixel to the next. Edge detecting an image significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. This was also stated in my Sobel and Laplace edge detection tutorial, but I just wanted reemphasize the point of why you would want to detect edges. The Canny edge detection algorithm is known to many as the optimal edge detector. Canny's intentions were to enhance the many edge detectors already out at the time he started his work. He was very successful in achieving his goal and his ideas and methods can be found in his paper, " A Computational Approach to Edge Detection ". In his paper, he followed a list of criteria to improve current methods of edge detection. The first and most obvious is low error rate. It is important that edges occuring in images should not be missed and that there be NO responses to non-edges. The second criterion is that the edge points be well localized. In other words, the distance between the edge pixels as found by the detector and the actual edge is to be at a minimum. A third criterion is to have only one response to a single edge. This was implemented because the first 2 were not substantial enough to completely eliminate the possibility of multiple responses to an edge.
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