Vehicle Number Plate Detection using Convolutional Neural Networks

  • Yash Patil
  • Krishna Mehta
  • Sopan Phaltankar
  • Dr. Reena Kumbhare

Abstract

Vehicle Number Plate Detection (VNPD) Security is one of the main concerns in today’s world. Every residential and government premises takes logs of the cars which enter their compounds. The manual logging of visiting vehicles in residential, commercial, government premises is cumbersome and expensive. An automated process for the same will greatly increase efficiency and reduce costs. This paper describes a seamless method for the same. The developed system will first detect the vehicle and then captures the vehicle image. Vehicle number plate region is extracted using 2D convolution. From the number plate obtained from the convolution the image frame is masked into grey scale. After masking, the trained model detects the texts in the frame and prints it on the screen.

Keywords: Image Processing, Convolution, Convolutional Neural Network, TensorFlow, OpenCV, Python

References

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[2] OpenCV - ”https://opencv.org/about.html”
[3] TensorFlow - https://www.tensorflow.org/
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How to Cite
Patil, Y., Mehta, K., Phaltankar, S., & Kumbhare, D. R. (2019). Vehicle Number Plate Detection using Convolutional Neural Networks. Asian Journal For Convergence In Technology (AJCT), 5(2). Retrieved from http://asianssr.org/index.php/ajct/article/view/868

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