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        OCR-based neural network for ANPR

        Author
        Zhai, Xiaojun
        Bensaali, Faycal
        Sotudeh, Reza
        Attention
        2299/9540
        Abstract
        Optical Character Recognition (OCR) is the last stage in an Automatic Number Plate Recognition System (ANPRs). In this stage the number plate characters on the number plate image are converted into encoded texts. In this paper, an Artificial Neural Network (ANN) based OCR algorithm for ANPR application is presented. A database of 3700 UK binary character images have been used for testing the performance of the proposed algorithm. Results achieved have shown that the proposed algorithm can meet the real-time requirement of an ANPR system and can averagely process a character image in 8.4ms with 97.3% successful recognition rate
        Publication date
        2012
        Published in
        Procs 2012 IEEE Int Conf on Imaging Systems and Techniques IST)
        Published version
        https://doi.org/10.1109/IST.2012.6295581
        Other links
        http://hdl.handle.net/2299/9540
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