Abstract
The article has been presented prototype system of recognizing a number of plates based on Raspberry Pi 2. The system was designed as the low-budget alternative to dear commercial solutions. This article is describing individual equipment components, the application controlling, the recognition process of the text and conducted examinations, showing the correctness of the reading. An applied algorithm has been described, as well as recognizing the text based on artificial neural networks.
References
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[2] http://www.raspberrypi-spy.co.uk/wp-content/uploads/2013/05/Raspberry-PiCamera-Module-Diagram.png
[3] https://www.raspberrypi.org/documentation/hardware/camera/README.md
[4] https://docs.google.com/document/d/1Y-yZnNhMYy7rwhAgyL_pfa39RsBx2qR4vP8saG73rE/edit
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[12] http://opencv.org/
[13] https://github.com/tesseract-ocr/tesseract/wiki
[2] http://www.raspberrypi-spy.co.uk/wp-content/uploads/2013/05/Raspberry-PiCamera-Module-Diagram.png
[3] https://www.raspberrypi.org/documentation/hardware/camera/README.md
[4] https://docs.google.com/document/d/1Y-yZnNhMYy7rwhAgyL_pfa39RsBx2qR4vP8saG73rE/edit
[5] http://www.postgresql.org.pl/
[6] Tadeusiewicz R.: Sieci neuronowe, Akademicka Oficyna Wydawnicza, Warszawa 1993.
[7] Clarke A.: OCR Functional Skills, Hodder & Stoughton, 2010.
[8] http://www.ftj.agh.edu.pl/~stegowski/rozne/neurony/art_kern_1.pdf
[9] Michalewicz Z.: Algorytmy genetyczne + struktury danych = programy ewolucyjne, Wydawnictwo WNT, 2003.
[10] Bradski G., Kaehler A.: Learning OpenCV Computer Vision with the OpenCV Library , Publisher: O'Reilly Media, Final Release Date: September 2008, Pages: 580.
[11] Mori S., Nishida H., Yamada H.: Optical Character Recognition, Authors: Publication: Cover Image Book Optical Character Recognition, 1st John Wiley & Sons, Inc. New York, USA, 1999, ISBN 0471308196.
[12] http://opencv.org/
[13] https://github.com/tesseract-ocr/tesseract/wiki