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@article{191766,
        author = {Rutuja Sapkal and Gayatri Bhojane and Renvi More},
        title = {Enhancing Automated Number Plate Recognition Using Optimized Character Segmentation and Deep Learning Models},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {8766-8768},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191766},
        abstract = {Automated Number Plate Recognition (ANPR) systems are crucial for intelligent traffic management and law enforcement. This paper presents a robust ANPR system optimized for moving vehicles under real-world conditions. The system employs image preprocessing, license plate localization, character segmentation, and recognition using deep learning techniques. Evaluation under motion blur, varying lighting, and damaged plates demonstrates improved recognition accuracy compared to traditional OCR methods such as Tesseract.},
        keywords = {ANPR, OCR, Deep Learning, Character Segmentation, Traffic Monitorin},
        month = {January},
        }