TITLE

基于 GPU+CPU 的 CANNY 算子快速实现

AUTHOR(S)
唐斌; 龙文
PUB. DATE
July 2016
SOURCE
Chinese Journal of Liquid Crystal & Displays;Jul2016, Vol. 31 Issue 7, p714
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This paper presents a fast method for Canny algorithm based on GPU+CPU. The Canny algorithm is divided into two parts:Gauss filtering, gradient computations, non maximum suppression and double thresholding are processed by GPU. The fast method convert two-dimensional Gaussian filter to two separable convolutions to reduce the computation complexity. Then, multiple threads execute kernel in parallel to speed up the computation in the CUDA program. Finally, threads access shared memory instead of global memory to hide the latencies of global memory. In addition, FIFO is used to connect components in CPU. The simulation results show that the processing time of the 8-bit images with the resolution 1 024×1 024 is 122 ms, which is 5.39 times faster than CPU. Therefore, this method takes full advantage of the parallelism of GPU and the serial processing capability of CPU.
ACCESSION #
118054383

 

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