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Edge Detection Algorithm Based on FPGA
- 1 School of Electronic and Information Engineering, Anhui University, Anhui, China
* Author to whom correspondence should be addressed.
Abstract
With the rapid development of computer technology Image processing is playing an increasingly important role in various fields. However, traditional edge detection algorithms are difficult to meet the needs of massive data volumes and the demands in scenarios with high real-time requirements. Therefore, the research topic of this paper is edge detection algorithm based on FPGA. This paper summarizes the existing edge detection algorithms based on FPGA, which have been studied by scholars both at home and abroad, and then implements five edge detection operators using Opencv computer vision library and Python. The author observed through research and comparing the results of five edge detection operators on images that the edges detected by the Roberts operator and Laplace operator were missing more seriously, while the Prewitt operator and Canny operator did not fully handle noise. The Sobel operator, compared to these four operators, had more continuous edge detection results and better detection ability for image details, as well as faster processing speed.
Keywords
Image Processing, Edge Detection, FPGA, Sobel
[1]. Zheng, H., Bai, Y., & Zhang, Y. (2020). An edge detection algorithm based on Sobel operator. Microcomputer Applications, 36(10), 4-6.
[2]. Li, D., Wu, Q., & Yang, H. (2022). Design and implementation of edge detection system based on improved Sobel operator. Information Technology and Network Security, 41(3), 13-17.
[3]. Wang, X., Chen, L., & Yan, B. (2023). Design and realization of image edge detection system based on FPGA in simulated low-light environment. Electronic Making, 31(11), 12-15.
[4]. Wang, Z., Shan, Y., Chu, C., et al. (2024). Improved edge detection algorithm and its FPGA implementation. Laser Journal, 45(3), 74-80.
[5]. Cha, J.-h. (2021). Research on real-time edge detection system based on FPGA (Master's thesis). Hefei University of Technology.
[6]. Wang, S. (2024). Improvement and realization of image processing edge detection algorithm based on FPGA (Master's thesis). Anhui Jianzhu University.
[7]. Zhou, Y. (2021). Design of real-time image acquisition and preprocessing system based on FPGA (Master's thesis). Huazhong University of Science and Technology.
[8]. Menaka, R., Janarthanan, R., & Deeba, K. (2020). FPGA implementation of low power and high speed image edge detection algorithm. Microprocessors and Microsystems, 75, 103053.
[9]. Li, T. (2024). An edge detection system based on FPGA improved Canny algorithm. Instrumentation Technology and Sensors, 8, 65-70.
[10]. Li, J., Liu, J., & Liu, Y. (2024). An improved Canny edge detection algorithm based on FPGA. Journal of Measurement Science and Instrumentation, 1-13.
Cite this article
Meng,Y. (2025). Edge Detection Algorithm Based on FPGA. Applied and Computational Engineering,120,193-197.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 5th International Conference on Signal Processing and Machine Learning
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