Implementing image processing algorithms using ‘Hardware in the loop’ approach for Xilinx FPGA

M. Kiran, Kan Mei War, Lim Mei Kuan, Liang Kim Meng, L. W. Kin
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引用次数: 20

Abstract

This paper outlines the investigation conducted in fine tuning the performance of our automated surveillance system. The constituent components of the system must have a processing speed of less than 40 ms. This is usually considered to be a standard timing constraint for most automated surveillance systems. To meet this constraint, it is important to quantify the reduction in processing speed that can be achieved if a component of the surveillance system is embedded onto a hardware based platform like an FPGA. A benchmark study was conducted to identify the component that contributed to the longest processing time in the entire system. Once the offending component was identified, its functionality was embedded onto the FPGA board using a combination of MATLAB-Simulink and Xilinx system generator prototyping environment. The results obtained indicated that the processing speed of the component was constantly faster on the FPGA platform as compared to MATLAB or C++ environment.
在Xilinx FPGA上使用“硬件在循环”方法实现图像处理算法
本文概述了在微调我们的自动监控系统的性能方面所进行的调查。系统各组成部件的处理速度必须小于40ms。这通常被认为是大多数自动监视系统的标准时间限制。为了满足这一限制,如果将监控系统的组件嵌入到基于硬件的平台(如FPGA)上,那么量化处理速度的降低是很重要的。进行了基准研究,以确定导致整个系统中处理时间最长的组件。一旦识别出问题组件,使用MATLAB-Simulink和Xilinx系统生成器原型环境的组合将其功能嵌入到FPGA板上。结果表明,在FPGA平台上,器件的处理速度不断快于MATLAB或c++环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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