Canny edge detection on NVIDIA CUDA
Perceptual Interfaces & Reality Lab., Maryland, Univ., College Park, MD
In 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (June 2008), pp. 1-8.
@conference{luo2008canny,
title={Canny edge detection on NVIDIA CUDA},
author={Luo, Y. and Duraiswami, R.},
booktitle={Computer Vision and Pattern Recognition Workshops, 2008. CVPRW’08. IEEE Computer Society Conference on},
pages={1–8},
year={2008},
organization={IEEE}
}
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 ldquotruerdquo edges, while suppressing ldquofalserdquo 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.
January 10, 2011 by hgpu
