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License Plate Character Recognition Using Binarization and Convolutional Neural Networks

  • Sandeep AngaraEmail author
  • Melvin RobinsonEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 943)

Abstract

The goal of an Automatic License Plate Recognition (ALPR) system is to capture and recognize a vehicle license plate. This is an important computer vision problem and has number of application domains: law enforcement, public safety agencies, and toll gate systems to name a few. At the heart of ALPR systems is the character recognition system as it is a unique identifier for any given vehicle. We construct an ALPR character recognition system by creating a dataset to simulate a captured license plate image, applying multiple binarization techniques to segment the characters from state, from the plate and from each other and finally using this dataset to train a convolutional neural network.

Keywords

Convolutional neural networks License plate recognition Deep learning Binarization 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of Texas at TylerTylerUSA

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