Abstract: Automated Number Plate Recognition (ANPR) is a crucial technology in smart transportation systems, law enforcement, and security monitoring. It involves the automated identification and reading of vehicle registration numbers from images or video feeds through the use of image analysis and machine learning techniques. The rapid increase in urban development and the growing number of vehicles on the roads have generated a significant need for effective, real-time number plate recognition systems to improve traffic management, decrease violations, and enhance public safety. This paper offers a summary of number plate detection techniques, concentrating on approaches such as edge detection, morphological operations, deep learning, and optical character recognition (OCR).
Older methods rely on feature extraction techniques like contour detection and colour segmentation, which perform well in controlled environments but struggle with variations in weather, lighting, and plate designs. Recent advancements in artificial intelligence, particularly deep learning through convolutional neural networks (CNNs), have led to remarkable improvements in the accuracy and robustness of number plate detection under varying conditions. The suggested system combines image preprocessing, plate localization, character segmentation, and OCR-based recognition to attain high detection precision. The implementation of deep learning models facilitates automatic feature extraction and classification, reducing the need for human involvement. Additionally, real-time execution utilizing edge computing and cloud-based processing improves the system’s overall efficiency. Applications of ANPR include automatic toll collection, enforcement of traffic laws, detection of stolen vehicles, management of parking, and control of access. Ongoing research is focused on addressing challenges like occlusions, blurry images, and inconsistencies in number plate formats. Future advancements may encompass hybrid AI models, integration of IoT-based smart surveillance, and advanced real-time processing techniques to further enhance detection accuracy and reliability.
Keywords: Number Plate Recognition, Vehicle registration.
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