Deep Learning Based Ethiopian Car’s License Plate Detection and Recognition

  • Ramasamy* D
  • et al.
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Abstract

Digital Image Processing is application of computer algorithms to process, manipulate and interpret images. As a field it is playing an increasingly important role in many aspects of people’s daily life. Even though Image Processing has accomplished a great deal on its own, nowadays researches are being conducted in using it with Deep Learning (which is part of a broader family, Machine Learning) to achieve better performance in detecting and classifying objects in an image. Car’s License Plate Recognition is one of the hottest research topics in the domain of Image Processing (Computer Vision). It is having wide range of applications since license number is the primary and mandatory identifier of motor vehicles. When it comes to license plates in Ethiopia, they have unique features like Amharic characters, differing dimensions and plate formats. Although there is a research conducted on ELPR, it was attempted using the conventional image processing techniques but never with deep learning. In this proposed research an attempt is going to be made in tackling the problem of ELPR with deep learning and image processing. Tensorflow is going to be used in building the deep learning model and all the image processing is going to be done with OpenCV-Python. So, at the end of this research a deep learning model that recognizes Ethiopian license plates with better accuracy is going to be built.

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Ramasamy*, Dr. A., & Wondwosen, Mr. J. (2020). Deep Learning Based Ethiopian Car’s License Plate Detection and Recognition. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 5730–5737. https://doi.org/10.35940/ijrte.f9857.038620

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