Abstract
Extraction of image edges is the basis of image processing class algorithms, for image edge extraction is of great significance. Nowadays, video image data is greatly increases the amount of image data and the processing difficulty. FPGA technology stands out for its parallel processing method and pipeline structure, which enables high-speed processing of large amounts of image data, and its high processing speed ensures real-time image data processing. The application of FPGA technology in the field of image data processing will be unstoppable. The main objective of this paper is to investigate the design and algorithms of a real-time image edge detection system using artificial intelligence and FPGAs. Median filtering and edge detection algorithms in video acquisition and pre-processing systems are an important part of complex algorithms in the field of target recognition and tracking, and the quality of image pre-processing plays an important role in the high accuracy of subsequent algorithms. This paper presents an in-depth study and analysis of the hardware implementation of the HD video capture and pre-processing system, combining the characteristics of FPGA parallel high-speed and pipeline structure, and completes the system design and verification on the hardware platform, fully proving the feasibility and correctness of the system.
Published Version
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