Automatic Number Plate Detection using Deep Learning and OCR

In recent years, the need for automated systems to recognize and process vehicle number plates has grown significantly due to increased security demands and traffic management needs. This paper presents a machine learning-based approach for number plate text detection. The proposed system employs a combination of convolutional neural networks (CNNs) for feature extraction and optical character recognition (OCR) for text detection and recognition. Initially, the system captures an image of the vehicle’s number plate, which is then pre-processed to enhance the image quality and isolate the number plate region. A trained CNN model is used to detect and extract the number plate from the image. Subsequently, OCR techniques are applied to the extracted number plate region to recognize and decode the alphanumeric characters. The proposed approach demonstrates high accuracy and robustness under various conditions, including different lighting, weather conditions, and plate designs