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Author:

Xie, Rong (Xie, Rong.) | Feng, Xiaoqin (Feng, Xiaoqin.)

Indexed by:

EI

Abstract:

Most of existing image processing algorithms have poor real-time performance in embedded device applications and occupy too much software resources. In this paper, a fast edge detection method is proposed based on Zynq platform. The xfOpenCv acceleration library provided by Xilinx is used to implement the edge detection algorithm. Specifically, the function operation process is accelerated in the FPGA through the acceleration constraint of a specific function implemented in the xfOpenCv library. In the implementation process, the SDx development environment is also used to simplify the function hardware acceleration development process. The experimental results show that our edge detection method takes less time than other methods, and has better real-time performance with the basically same detection results. © 2018 IEEE.

Keyword:

Cloud computing Edge detection Image processing Internet of things Application programs

Author Community:

  • [ 1 ] [Xie, Rong]Beijing University of Technology, Department of Information, Beijing, China
  • [ 2 ] [Feng, Xiaoqin]Beijing University of Technology, Department of Information, Beijing, China

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Source :

Year: 2018

Page: 468-471

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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