Character recognition builds a recognizing factor for identifying the accuracy in characters. The accuracy of classifying the recognizing characters in an image is applied through deep learning methods. The character recognition is mainly focusing on the layers of text recognition through deep learning techniques. Well cleared python code assists to furnish all the levels of image by following deep learning that algorithmically analyse and recognize text from the given input image. This research work has been proposed for recognizing characters using deep learning techniques and recognize the input image with well-furnished and most efficient output. It provides a high level of accuracy-built output after the recognition of characters in the high-resolution image. This recognized character can be converted into user desired languages where the proposed model is trained to recognize some particular languages.


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    Title :

    Character Recognition using Tesseract enabling Multilingualism




    Publication date :

    2020-11-05


    Size :

    523634 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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