One of the most significant methods utilized in the deep learning approach is text recognition. Text recognition is now a very significant activity that is utilized in many applications of current gadgets to recognize images in a detailed manner. Automatic number plate recognition, for example, is an image processing approach that detects the vehicle's number (license) plate. The automatic number plate recognition system (ANPR) is a key feature that is used to manage traffic congestion. The goal of ANPR is to devise a method for automatically identifying permitted vehicles using vehicle numbers. Automatic number plate recognition (ANPR) is utilized in a variety of applications, including traffic control, vehicle tracking, and automatic payment of tolls on roads and bridges, as well as monitoring systems, parking management systems, and toll collecting stations. The established approach first recognizes the vehicle before taking a picture of it. After that, the number plate region in the car is localized using a neural network, and the image is segmented. Using a character recognition approach, characters are retrieved from the plate. The results, together with the time stamp, are then saved in the database. It is implemented and performed in Python, and the results are tested on a real picture.


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    Titel :

    Text Recognition from Images Using Deep Learning Techniques


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Rao, B. Narendra Kumar (Herausgeber:in) / Balasubramanian, R. (Herausgeber:in) / Wang, Shiuh-Jeng (Herausgeber:in) / Nayak, Richi (Herausgeber:in) / Narendra Kumar Rao, B. (Autor:in) / Pranitha, Kondra (Autor:in) / Ranjana (Autor:in) / Krishnaveni, C. V. (Autor:in) / Chakkaravarthy, Midhun (Autor:in)


    Erscheinungsdatum :

    14.11.2022


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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