Model-based Design of a High-Throughput Canny Edge Detection Accelerator on Zynq-7000 FPGA

Authors

  • Ahmed Alhomoud Department of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Saudi Arabia
  • Refka Ghodhbani Department of Computer Sciences, Faculty of Computing and information Technology, Northern Border University, Saudia Arabia | Electronics and Micro-Electronics Laboratory, Faculty of Sciences, Monastir University, Tunisia
  • Taoufik Saidani Department of Computer Sciences, Faculty of Computing and information Technology, Northern Border University, Saudi Arabia | Electronics and Micro-Electronics Laboratory, Faculty of Sciences, Monastir University, Tunisia
  • Hafedh Mahmoud Zayani Department of Electrical Engineering, College of Engineering, Northern Border University, Saudi Arabia
  • Yahia Said Department of Electrical Engineering, College of Engineering, Northern Border University, Saudi Arabia
  • Mohamed Ben Ammar Department of Information Systems, Faculty of Computing and Information Technology, Northern Border, Saudi Arabia
  • Jihane Ben Slimane Department of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Saudi Arabia
Volume: 14 | Issue: 2 | Pages: 13547-13553 | April 2024 | https://doi.org/10.48084/etasr.7081

Abstract

This paper presents a novel approach for fast FPGA prototyping of the Canny edge detection algorithm using High-Level Synthesis (HLS) based on the HDL Coder. Traditional RTL-based design methodologies for implementing image processing algorithms on FPGAs can be time-consuming and error-prone. HLS offers a higher level of abstraction, enabling designers to focus on algorithmic functionality while the tool automatically generates efficient hardware descriptions. This advantage was exploited by implementing the Canny edge detection algorithm in MATLAB/Simulink and utilizing the HDL Coder to automatically convert it into synthesizable VHDL code. This design flow significantly reduces development time and complexity compared to the traditional RTL approach. The experimental results showed that the HLS-based Canny edge detector achieved real-time performance on a Xilinx FPGA platform, showcasing the effectiveness of the proposed approach for fast FPGA prototyping in image processing applications.

Keywords:

FPGA, high-level synthesis, HDL coder, Canny edge detection, image processing, fast prototyping

Downloads

Download data is not yet available.

References

J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, "You Only Look Once: Unified, Real-Time Object Detection," in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2016, pp. 779–788.

R. Ghodhbani, T. Saidani, A. Alhomoud, A. Alshammari, and R. Ahmed, "Real Time FPGA Implementation of an Efficient High Speed Harris Corner Detection Algorithm Based on High-Level Synthesis," Engineering, Technology & Applied Science Research, vol. 13, no. 6, pp. 12169–12174, Dec. 2023.

T. Saidani and R. Ghodhbani, "Hardware Acceleration of Video Edge Detection with Hight Level Synthesis on the Xilinx Zynq Platform," Engineering, Technology & Applied Science Research, vol. 12, no. 1, pp. 8007–8012, Feb. 2022.

T. Saidani, R. Ghodhbani, A. Alhomoud, A. Alshammari, H. Zayani, and M. B. Ammar, "Hardware Acceleration for Object Detection using YOLOv5 Deep Learning Algorithm on Xilinx Zynq FPGA Platform," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 13066–13071, Feb. 2024.

CongJason et al., "FPGA HLS Today: Successes, Challenges, and Opportunities," ACM Transactions on Reconfigurable Technology and Systems (TRETS), Aug. 2022.

Z. Tan and J. S. Smith, "Real-time Canny Edge Detection on FPGAs using High-level Synthesis," in 2020 7th International Conference on Information Science and Control Engineering (ICISCE), Sep. 2020, pp. 1068–1071.

A. Fuentes-Alventosa, J. Gómez-Luna, and R. Medina-Carnicer, "GUD-Canny: a real-time GPU-based unsupervised and distributed Canny edge detector," Journal of Real-Time Image Processing, vol. 19, no. 3, pp. 591–605, Jun. 2022.

F. Siddiqui et al., "FPGA-Based Processor Acceleration for Image Processing Applications," Journal of Imaging, vol. 5, no. 1, Jan. 2019, Art. no. 16.

P. Babu and E. Parthasarathy, "Hardware acceleration for object detection using YOLOv4 algorithm on Xilinx Zynq platform," Journal of Real-Time Image Processing, vol. 19, no. 5, pp. 931–940, Oct. 2022.

F. N. Taher, M. Kishani, and B. C. Schafer, "Design and Optimization of Reliable Hardware Accelerators: Leveraging the Advantages of High-Level Synthesis," in 2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS), Platja d’Aro, Spain, Jul. 2018, pp. 232–235.

“AXI4-Stream Video IP and System Design Guide,” Xilinx, UG934, Oct. 2019.

Stephen Neuendorffer, Thomas Li, and Devin Wang, "Accelerating OpenCV Applications with Zynq-7000 All Programmable SoC using Vivado HLS Video Libraries," Xilinx, Aug. 2013.

K. Kintali and Y. Gu, "Model-Based Design with Simulink, HDL Coder, and Xilinx System Generator for DSP," Mathworks, 2015.

S. Liu et al., "Real-time implementation of harris corner detection system based on FPGA," in 2017 IEEE International Conference on Real-time Computing and Robotics (RCAR), Jul. 2017, pp. 339–343.

S. Chumpol, P. Solod, K. Thongnoo, and N. Jindapetch, "Model-Based Design Optimization using CDFG for Image Processing on FPGA," ECTI Transactions on Computer and Information Technology (ECTI-CIT), vol. 17, no. 4, pp. 479–487, Oct. 2023.

S. Titri, C. Larbes, and K. Y. Toumi, "Rapid prototyping of PVS into FPGA: From model based design to FPGA/ASICs implementation," in 2014 9th International Design and Test Symposium (IDT), Algeries, Algeria, Dec. 2014, pp. 162–167.

I. El Hajjouji, S. Mars, Z. Asrih, and A. El Mourabit, "A novel FPGA implementation of Hough Transform for straight lane detection," Engineering Science and Technology, an International Journal, vol. 23, no. 2, pp. 274–280, Apr. 2020.

Downloads

How to Cite

[1]
A. Alhomoud, “Model-based Design of a High-Throughput Canny Edge Detection Accelerator on Zynq-7000 FPGA”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 2, pp. 13547–13553, Apr. 2024.

Metrics

Abstract Views: 251
PDF Downloads: 343

Metrics Information

Most read articles by the same author(s)

<< < 1 2