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@article{200253,
        author = {Gauri Sunil Shirsath and Gayatri Madhukar Kate and Ujwala Pralhad Gaikwad and Manjusha Shivaji Jadhav and Prof. Kurhe P. V.},
        title = {Automated Vehicle Number Plate Detection and logging system},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {3870-3873},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200253},
        abstract = {Automatic License Plate Recognition (ALPR) systems are widely used in traffic monitoring, parking management, toll collection, and security applications. This paper presents a Smart Automatic License Plate Recognition System using YOLOv8 and EasyOCR for real-time vehicle number plate detection and text extraction. The proposed system integrates a custom-trained YOLOv8 model for accurate plate localization and EasyOCR for optical character recognition. A Flask-based web application is developed to provide live camera streaming, uploaded video processing, and real-time logging of detected license plates. SQLite database is used for maintaining historical records. The system supports multi-platform deployment and offers an efficient, low-cost, and scalable solution for smart surveillance systems.},
        keywords = {ALPR, YOLOv8, EasyOCR, Computer Vision, Flask, Vehicle Detection, OCR, Deep Learning},
        month = {May},
        }