International Journal For Multidisciplinary Research

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Helmet Detection And Number Plate Recognition Using YOLOV5

Author(s) PAPPALA THANMAI, T. V. S. SRI RAM, TATAVOLU DURGA SRIYA, NAKKA NOOKARATNAM, VARADA NAGA SUBA AMRUTHA
Country India
Abstract Helmet usage is crucial for motorcycle riders to ensure their safety on roads. Moreover, enforcing traffic regulations, such as identifying vehicles without helmets and recognizing their license plates, aids in maintaining road safety and law enforcement. In this project, we propose a robust system for helmet detection and number plate recognition specifically tailored for motorcycles. We utilize the YOLOv5 object detection model to detect motorcycles in images or videos, followed by identifying whether riders are wearing helmets or not. If a rider is detected without a helmet, the system proceeds to recognize the motorcycle's license plate using optical character recognition (OCR). We employ EasyOCR, a Python-based OCR library, to extract text from the license plate images and save the information into a CSV file for further processing. The proposed system provides a comprehensive solution for enhancing road safety and enforcing traffic regulations concerning helmet usage and license plate recognition for motorcycles.
Keywords Helmet detection, Number plate recognition, Motorcycle safety, YOLOv5 object detection, Optical character recognition (OCR), EasyOCR library, Road safety, Traffic regulations, Law enforcement, CSV file processing.
Field Engineering
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-30
Cite This Helmet Detection And Number Plate Recognition Using YOLOV5 - PAPPALA THANMAI, T. V. S. SRI RAM, TATAVOLU DURGA SRIYA, NAKKA NOOKARATNAM, VARADA NAGA SUBA AMRUTHA - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.18612
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.18612
Short DOI https://doi.org/gtsnvp
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