Computer Science ›› 2019, Vol. 46 ›› Issue (11A): 289-293.

• Pattern Recognition & Image Processing • Previous Articles     Next Articles

Parallel Harris Feature Point Detection Algorithm

ZHU Chao, WU Su-ping   

  1. (School of Information Engineering,Ningxia University,Yinchuan 750021,China)
  • Online:2019-11-10 Published:2019-11-20

Abstract: Harris Feature point detection is widely used in target recognition,tracking and 3D reconstruction.The computation of the feature point detection algorithm for big data problem is time-consuming and computation-intensive.There is a problem of large time-consuming and low efficiency in the algorithm of feature points detection with large data quantity.In the multi-CPU programming model based on OpenMP and GPU parallel environment based on CUDA and OpenCL architecture,In this paper,the parallel algorithm of the Harris feature point detection was proposed.In the comparison experiment of hallFeng image set on different platforms,the experimental results show that the multi-CPU feature point detection algorithm based on OpenMP shows good multi-core scalability,and the parallel feature point detection algorithms based on CUDA and OpenCL architecture in GPU parallel environment can obtain high speedup and good data and platform scalability,the maximum speed up can be more than 90 times,and the acceleration effect is significant.

Key words: Compute unified device architecture (CUDA), Feature point detection, Harris, Open computing language (OpenCL), Open multi-processing(OpenMP), Parallel algorithm

CLC Number: 

  • TP391
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