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author:

Lin, C. (Lin, C..) [1] | Qian, H. (Qian, H..) [2] | Wang, Z. (Wang, Z..) [3]

Indexed by:

Scopus

Abstract:

To tackle the problem of inadequate performance in data processing on existing embedded systems, in this paper, we present a well-optimized parallel image processing scheme based on the NEON acceleration engine. It targets at the Prewitt operator, a classical image edge processing method with good properties including high precision and strong anti-noise ability. However, it requires a high computational cost and leads to insufficient real-Time processing capability. In this work, by exploring the parallel processing characteristics of the NEON engine, we concatenate R, G, B three-channel data in parallel, optimize the data processing schedule of the Prewitt operator and implement the real-Time video processing on Xilinx's Zynq-7010 all programmable system-on-chip (APSOC) development platform. Experimental results demonstrate that the proposed design can achieve approximate 4 times speedup compared to a regular design using ARM C library. It is almost 2 orders of magnitude faster than using ARM Coretex-A9 without NEON. © 2018 IEEE.

Keyword:

Data Parallel Optimization; Edge detection; NEON+ARM; Rescheduling

Community:

  • [ 1 ] [Lin, C.]Fujian Key Laboratory of IoT Engineering and Application, Fuzhou University, United States
  • [ 2 ] [Qian, H.]Fujian Key Laboratory of IoT Engineering and Application, Fuzhou University, United States
  • [ 3 ] [Wang, Z.]Nanjing University, China

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Source :

2018 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2018

Year: 2019

Page: 270-273

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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