CHARACTER RECOGNITION FOR INDONESIAN LICENSE PLATE BY USING IMAGE ENHANCEMENT AND CONVOLUTIONAL NEURAL NETWORK

Authors

  • Sahid Bismantoko Center of Technology for System and Infrastructure of Transportation Agency for the Assessment and Application of Technology
  • Umi Chasanah Center of Technology for System and Infrastructure of Transportation Agency for the Assessment and Application of Technology
  • Adityo Suksmono Center of Technology for System and Infrastructure of Transportation Agency for the Assessment and Application of Technology
  • Tri Widodo Center of Technology for System and Infrastructure of Transportation Agency for the Assessment and Application of Technology

DOI:

https://doi.org/10.29122/mipi.v14i2.4198

Keywords:

ALPR, ITS, Recall, Precision, F-1 Score, Accuracy, Loss

Abstract

Many Intelligent Transport System technology have been applied in real world problems such as traffic monitoring, parking management, toll collection, law enforcement. ALPR system is one of the ITS technologies that is widely applied, however this ALPR system can not produce faultless recognition yet, especially for Indonesia license plate. In this research, image enhancement and Convolution Neural Network are proposed to the character recognition. The dataset used in this research are Indonesia license plate. The first step is train dataset to recognize character and evaluate the model with recall, precision, and f-1 score from test dataset. The model achieves accuracy and loss just over 0.99 and just below 0.01 on validation dataset respectively.

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Published

13-09-2023

How to Cite

Bismantoko, S., Chasanah, U., Suksmono, A., & Widodo, T. (2023). CHARACTER RECOGNITION FOR INDONESIAN LICENSE PLATE BY USING IMAGE ENHANCEMENT AND CONVOLUTIONAL NEURAL NETWORK. Majalah Ilmiah Pengkajian Industri; Journal of Industrial Research and Innovation, 14(2), 145–152. https://doi.org/10.29122/mipi.v14i2.4198