液晶与显示2016，Vol.31Issue(7)：714-720,7.DOI:10.3788/YJYXS20163107.0714
基于 GPU＋CPU 的 CANNY 算子快速实现
Fast Canny algorithm based on GPU + CPU
摘要
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.关键词
CANNY/CUDA/GPU/加速Key words
Canny/CUDA/GPU/acceleration分类
信息技术与安全科学引用本文复制引用
唐斌,龙文..基于 GPU＋CPU 的 CANNY 算子快速实现[J].液晶与显示,2016,31(7):714-720,7.基金项目
国家自然科学基金(No．61463009) Supported by National Natural Science Foundation of China(No．61463009) （No．61463009）
