A novel deep learning-based method for vehicle model and number plate detection in camera-captured blurred video using YOLOv5, EasyOCR, and ResNet50

This research presents a deep learning-based system for vehicle identification, combining Vehicle Make and Model Recognition (VMMR) with Automatic Number Plate Recognition (ANPR). Unlike traditional methods that handle each task separately, the integrated approach offers a more efficient and reliable solution, even in challenging weather conditions. The system utilizes MobileNet-V2, YOLOx, YOLOv4-tiny, Paddle OCR, and SVTR-tiny, and is tested on diverse real-world images. Additionally, we have successfully handled blurred inputs captured from video and live camera streams, enhancing the system’s robustness in real-time scenarios. Results show robust performance, with further insights gained through Grad Cam technology to improve accuracy. The study’s findings have significant implications for applications in autonomous driving, traffic management, and security enforcement.