Efficient Vehicle Registration Recognition System: Enhancing Accuracy and Power Efficiency through Digital Image Processing

R. Madhumitha (1)
(1) Department of Electronics and Communication Engineering, St.Joseph’s College of Engineering, OMR, Chennai-600119, India
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How to cite (IJASEIT) :
R. Madhumitha. (2024). Efficient Vehicle Registration Recognition System: Enhancing Accuracy and Power Efficiency through Digital Image Processing . International Journal of Advanced Science Computing and Engineering, 6(2), 74–79. https://doi.org/10.62527/ijasce.6.2.206

Number-plate recognition technology uses optical character recognition on images to read vehicle registration plates using OpenCV, PyTesseract OCR Engine, and YOLOv4 model. Images of the license plates are provided to the YOLOv4 model using a web app. The model is trained with the help of images from the Kaggle dataset. Then the number plate is extracted from the vehicle using the model. The string from the image is extracted using PyTesseract OCR Engine. Tested on several datasets this method gave us a success rate of 94%. This method can also be used in real-time incidents.

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