Hardware Acceleration of Video Edge Detection with Hight Level Synthesis on the Xilinx Zynq Platform
Received: 12 November 2021 | Accepted: 1 December 2021 | Online: 18 December 2021
Corresponding author: T. Saidani
Abstract
The study conducted in the current paper consists of validating an original design flow for the rapid prototyping of real-time image and video processing applications on FPGAs. A video application for edge detection with Simulink HDL coder and Vivado High-Level Synthesis (HLS) has been designed as if the code was going to be executed on a conventional processor. The developed tools will automatically translate the code into VHDL hardware language using an advanced compilation technique. This amounts to embedding processors on Xilinx Zynq-7000 System on-Chip (SoC) device in an optimal manner. This automated hardware design flow reduces the time to create a prototype since only the high-level description is required. The design of the video edge detection system is implemented on Xilinx Zynq-7000 platform. The result of the implementation gave effective resource utilization and a good frame rate (95 FPS) under 170MHz frequency.
Keywords:
high-level synthesis, automated hardware design, co-design, Xilinx Zynq-7000Downloads
References
H. M. Abdelgawad, M. Safar, and A. M. Wahba, "High Level Synthesis of Canny Edge Detection Algorithm on Zynq Platform," International Journal of Computer and Information Engineering, vol. 9, no. 1, pp. 148–152, Jan. 2015.
T. T. Duong, J. H. Seo, T. D. Tran, B. J. Young, and J. W. Jeon, "Evaluation of Embedded Systems for Automotive Image Processing," in 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Busan, Korea (South), Jun. 2018, pp. 123–128. DOI: https://doi.org/10.1109/SNPD.2018.8441073
C. Li, Y. Bi, F. Marzani, and F. Yang, "Fast FPGA prototyping for real-time image processing with very high-level synthesis," Journal of Real-Time Image Processing, vol. 16, no. 5, pp. 1795–1812, Oct. 2019. DOI: https://doi.org/10.1007/s11554-017-0688-1
M. B. Ayed, S. Elkosantini, and M. Abid, "An Automated Surveillance System Based on Multi-Processor and GPU Architecture," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2319–2323, Dec. 2017. DOI: https://doi.org/10.48084/etasr.1645
Arjona, R., Baturone, I., 2020. Using Simulink HDL Coder to implement a Fingerprint Recognition Algorithm into an FPGA, in: 2020 XIV Technologies Applied to Electronics Teaching Conference (TAEE). Presented at the 2020 XIV Technologies Applied to Electronics Teaching Conference (TAEE), Porto, Portugal. DOI: https://doi.org/10.1109/TAEE46915.2020.9163790
H. Mestiri, I. Barraj, and M. Machhout, "AES High-Level SystemC Modeling using Aspect Oriented Programming Approach," Engineering, Technology & Applied Science Research, vol. 11, no. 1, pp. 6719–6723, Feb. 2021. DOI: https://doi.org/10.48084/etasr.3971
L. Zouari, S. Chtourou, M. B. Ayed, and S. A. Alshaya, "A Comparative Study of Computer-Aided Engineering Techniques for Robot Arm Applications," Engineering, Technology & Applied Science Research, vol. 10, no. 6, pp. 6526–6532, Dec. 2020. DOI: https://doi.org/10.48084/etasr.3885
T. Han, G. W. Liu, H. Cai, and B. Wang, "The face detection and location system based on Zynq," in 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Xiamen, China, Aug. 2014, pp. 835–839. DOI: https://doi.org/10.1109/FSKD.2014.6980946
A. Alsheikhy and Y. F. Said, "Design of Embedded Vision System based on FPGA-SoC," International Journal of Advanced Computer Science and Applications, vol. 10, no. 10, 2019. DOI: https://doi.org/10.14569/IJACSA.2019.0101013
J. Jiang, C. Liu, and S. Ling, "An FPGA implementation for real-time edge detection," Journal of Real-Time Image Processing, vol. 15, no. 4, pp. 787–797, Dec. 2018. DOI: https://doi.org/10.1007/s11554-015-0521-7
R. Ghodhbani, L. Horrigue, T. Saidani, and M. Atri, "Fast FPGA Prototyping based Real-Time Image and Video Processing with High-Level Synthesis," International Journal of Advanced Computer Science and Applications, vol. 11, no. 2, 2020. DOI: https://doi.org/10.14569/IJACSA.2020.0110215
"HDL Coder Evaluation Reference Guide," Mathworks. https://nl.mathworks.com/matlabcentral/fileexchange/58941-hdl-coder-evaluation-reference-guide (accessed Dec. 08, 2021).
"Accelerate Design Space Exploration Using HDL Coder Optimizations - Video," Mathworks. https://nl.mathworks.com/videos/accelerate-design-space-exploration-using-hdl-coder-optimizations-81998.html (accessed Dec. 08, 2021).
L. H. Crockett, R. A. Elliot, M. A. Enderwitz, and R. W. Stewart, The Zynq Book: Embedded Processing with the Arm Cortex-A9 on the Xilinx Zynq-7000 All Programmable Soc. Glasgow, UK: Strathclyde Academic Media, 2014.
Introduction to FPGA Design with Vivado High-Level Synthesis (UG998). Xilinx, 2019.
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