Real-time Detection System of Vehicle License Plate in Complex Environment Based on Multi-Modal Image Fusion

To meet the needs of intelligent transportation systems and autonomous driving for real-time and precise vehicle target detection, this study focuses on the application of multimodal image fusion technology in real-time vehicle license plate detection systems under complex environments, addressing the problems of high hardware costs and large transmission delays in traditional detection methods. A lightweight embedded vision system based on FPGA and OV5640 camera is proposed to achieve efficient recognition and detection of vehicle targets. This design clarifies the application value of multimodal image fusion technology in intelligent transportation systems; then deeply analyzes the characteristics and classification of multimodal mages, as well as the methods and strategies of image fusion. On this basis, a real-time vehicle license plate detection system in complex environments is constructed, covering system architecture design, algorithm optimization, performance improvement, and FPGAbased data packaging and flow control strategies. Through detailed experimental design and data collection, the performance of the detection system is systematically evaluated and analyzed. The research results not only promote the development of multimodal image fusion technology, but also provide theoretical support and technical guarantee for the practical application of intelligent transportation systems.