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@article{170630,
        author = {Rajesh Kumar and Ashima},
        title = {Detailed Analysis of Vehicle Number Plate Text  Extraction Through Image},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {820-824},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170630},
        abstract = {Over the past few years, automatic number plate detection systems have become more common in security, safety, and business environments. Computer vision is utilized for number plate detection in order to give quick and precise identification. Utilizing Deep Learning (DL) techniques, numerous computational methods have recently been created for the recognition of automobile registration information based on number plates. In the proposed structure, we used optical character recognition (OCR) and a new deep learning-based technique for automatic number plate detection and recognition. The initial structures should have been configured with pictures of every character and have a single content style. For the majority of content styles, pushed structures designed to communicate an abnormal level of acknowledgment precision are now common. A few buildings, including sections, images, and other non-printed elements, are ready to be used to recreate sorted-out result that closely resembles the main page.},
        keywords = {Number plat detection; recognition; deep learning; OCR; image classification},
        month = {December},
        }