Automated License Plate Recognition Using Artificial Intelligence: A Comprehensive Review of Advances in the Last Decade

Automated License Plate Recognition has evolved from a niche computer vision task into a cornerstone technology for intelligent transportation systems (ITS), security, and urban management. This paper provides a comprehensive review of image processing techniques and artificial intelligence (AI) methodologies employed in ALPR systems over the past ten years. The paradigm shift from traditional handcrafted feature-based approaches to deep learning architectures, particularly Convolutional Neural Networks (CNNs) and hybrid models, has led to unprecedented gains in accuracy, robustness, and processing speed. This article systematically analyzes these evolving architectures, including object detection frameworks, sequence recognition models, and vision transformers. It details the challenges posed by real-world variabilities such as illumination, viewpoint, and plate degradation, and surveys the corresponding AI-driven solutions. Furthermore, the paper reviews established public benchmarks, evaluation metrics, and practical implementation considerations. Finally, it discusses current limitations and outlines emerging trends, including edge computing, federated learning, and privacy-preserving Automated License Plate Recognition, providing a roadmap for future research and development in this critical field. Many license plate systems work only when images are clear and bright. But in real life - for example at night or when the camera moves - the image gets blurry or dark. My project solves this problem. First, it improves the image - it removes blur, fixes the light and contrast automatically. Then, a small machine-learning model reads the numbers and letters on the plate. The system can read plates with over ۹۰ percent accuracy, even when images are not clear. It also works on small devices, so it doesn't need expensive hardware. This technology can help traffic control, parking systems, and smart city projects. In short, we combine image enhancement and AI recognition to make a smart and reliable system.

کلیدواژه ها:

smart ، reliable system ، Automated License Plate ، Recognition