In the previous chapter, we learned how it is possible to detect the edges of an image. In particular, we showed you that by applying a threshold on the gradient magnitude, a binary map of the main edges of an image can be obtained. Edges carry important visual information since they delineate the image elements. For this reason, they can be used, for example, in object recognition. However, simple binary edge maps suffer from two main drawbacks. First, the edges that are detected are unnecessarily thick; this makes the object's limit more difficult to identify. Second, and more importantly, it is often impossible to find a threshold that is sufficiently low in order to detect all important edges of an image and is, at the same time, sufficiently high in order to not include too many insignificant edges. This is a trade-off problem that the Canny algorithm tries to solve.
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You're reading from OpenCV Computer Vision Application Programming Cookbook Second Edition
Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content based video analysis, visual surveillance, driver-assistance, object detection, and tracking.
Robert authored the OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development published by McGraw Hill in 2001. He co-founded Visual Cortek in 2006, an Ottawa-based video analytics start-up that was later acquired by iwatchlife.com in 2009. He is also a consultant in computer vision and has assumed the role of Chief Scientist in a number of start-up companies such as Cognivue Corp, iWatchlife, and Tempo Analytics.
Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and MSc and PhD degrees from INRS-Telecommunications, Montreal (1996). You can visit the author's website at laganiere.name.
Read more about Robert Laganiere
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Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content based video analysis, visual surveillance, driver-assistance, object detection, and tracking.
Robert authored the OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development published by McGraw Hill in 2001. He co-founded Visual Cortek in 2006, an Ottawa-based video analytics start-up that was later acquired by iwatchlife.com in 2009. He is also a consultant in computer vision and has assumed the role of Chief Scientist in a number of start-up companies such as Cognivue Corp, iWatchlife, and Tempo Analytics.
Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and MSc and PhD degrees from INRS-Telecommunications, Montreal (1996). You can visit the author's website at laganiere.name.
Read more about Robert Laganiere