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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Canny edge detection on NVIDIA CUDA
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Yuancheng Luo, Perceptual Interfaces and Reality Laboratory, Computer Science&UMIACS, University of Maryland, College Park, USA
Ramani Duraiswami, Perceptual Interfaces and Reality Laboratory, Computer Science&UMIACS, University of Maryland, College Park, USA
The Canny edge detector is a very popular and effective edge feature detector that is used as a pre-processing step in many computer vision algorithms. It is a multi-step detector which performs smoothing and filtering, non-maxima suppression, followed by a connected-component analysis stage to detect “true” edges, while suppressing “false” non edge filter responses. While there have been previous (partial) implementations of the Canny and other edge detectors on GPUs, they have been focussed on the old style GPGPU computing with programming using graphical application layers. Using the more programmer friendly CUDA framework, we are able to implement the entire Canny algorithm. Details are presented along with a comparison with CPU implementations. We also integrate our detector in to MATLAB, a popular interactive simulation package often used by researchers. The source code will be made available as open source.
Citation:
Yuancheng Luo, Ramani Duraiswami, "Canny edge detection on NVIDIA CUDA," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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