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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 2, 2020.
Abstract: Programming in high abstraction level is known by its benefits. It can facilitate the development of digital image and video processing systems. Recently, high-level synthesis (HLS) has played a significant role in developing this field of study. Real time image and video Processing solution needing high throughput rate are often performed in a dedicated hardware such as FPGA. Previous studies relied on traditional design processes called VHDL and Verilog and to synthesize and validate the hardware. These processes are technically complex and time consuming. This paper introduces an alternative novel approach. It uses a Model-Based Design workflow based on HDL Coder (MBD), Vision HDL Toolbox, Simulink and MATLAB for the purpose of accelerating the design of image and video solution. The main purpose of the present paper is to study the complexity of the design development and minimize development time (Time to market: TM) of conventional FPGA design. In this paper, the complexity of the development™ can be reduced by 60% effectively by automatically generating the IP cores and downloading the modeled design through the Xilinx tools and give more advantages of FPGA related to the other devices like ASIC and GPU.
Refka Ghodhbani, Layla Horrigue, Taoufik Saidani and Mohamed Atri, “Fast FPGA Prototyping based Real-Time Image and Video Processing with High-Level Synthesis” International Journal of Advanced Computer Science and Applications(IJACSA), 11(2), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110215
@article{Ghodhbani2020,
title = {Fast FPGA Prototyping based Real-Time Image and Video Processing with High-Level Synthesis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110215},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110215},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {2},
author = {Refka Ghodhbani and Layla Horrigue and Taoufik Saidani and Mohamed Atri}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.