Model-Based Design Optimization using CDFG for Image Processing on FPGA

Q4 Decision Sciences
Surachate Chumpol, Panadda Solod, Krerkchai Thongnoo, Nattha Jindapetch
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引用次数: 0

Abstract

As the automotive industry moves toward autonomous driving and ADAS (Advanced Driver Assistance Systems), Model-Based Design (MBD) is a practical design methodology. It can be used to develop rapid prototyping by using MATLAB and Simulink. The MBD method still has limitations for handling complex models. This paper uses the Control Data Flow Graph (CDFG), an intermediate representation for analyzing complex algorithms, so that suitable optimizations for image processing applications can be implemented on an FPGA. The experimental results show that the proposed CDFG method improved both the area and speed of the edge detection case study compared with the MathWorks Vision HDL toolbox.
基于模型的CDFG FPGA图像处理优化设计
随着汽车行业向自动驾驶和高级驾驶辅助系统(ADAS)发展,基于模型的设计(MBD)成为一种实用的设计方法。它可以用于MATLAB和Simulink的快速原型开发。MBD方法在处理复杂模型时仍有局限性。本文使用控制数据流图(CDFG),一种用于分析复杂算法的中间表示,以便在FPGA上实现适合图像处理应用的优化。实验结果表明,与MathWorks Vision HDL工具箱相比,所提出的CDFG方法提高了边缘检测案例研究的面积和速度。
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来源期刊
ECTI Transactions on Computer and Information Technology
ECTI Transactions on Computer and Information Technology Engineering-Electrical and Electronic Engineering
CiteScore
1.20
自引率
0.00%
发文量
52
审稿时长
15 weeks
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