Recognition of Korean Alphabet (Hangul) Handwriting into Latin Characters Using Backpropagation Method

  • Anang Aris Widodo Informatics Engineering Department, University of Merdeka Pasuruan
  • Muchammad Yuska Izza Mahendra Informatics Engineering Department, University of Merdeka Pasuruan
  • Mohammad Zoqi Sarwani Informatics Engineering Department, University of Merdeka Pasuruan
https://doi.org/10.25139/ijair.v3i2.4210
Abstract views: 322 , PDF downloads: 279
Keywords: Korea, Hangul, Backpropagation Method, Artificial Neural Network

Abstract

The popularity of Korean culture today attracts many people to learn everything about Korea, especially in learning the Korean language. To learn Korean, you must first know Korean letters (Hangul), which are non-Latin characters. Therefore, a digital approach is needed to recognize handwritten Korean (Hangul) words easily. Handwritten character recognition has a vital role in pattern recognition and image processing for handwritten Character Recognition (HCR). The backpropagation method trains the network to balance the network's ability to recognize the patterns used during training and the network's ability to respond correctly to input patterns that are similar but not the same as the patterns used during training. This principle is used for character recognition of Korean characters (Hangul), a sub-topic in fairly complex pattern recognition. The results of the calculation of the backpropagation artificial neural network with MATLAB in this study have succeeded in identifying 576 image training data and 384 Korean letter testing data (Hangul) quite well and obtaining a percentage result of 80.83% with an accuracy rate of all data testing carried out on letters. Korean (Hangul).

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Published
2021-11-30
How to Cite
Anang Aris Widodo, Muchammad Yuska Izza Mahendra, & Mohammad Zoqi Sarwani. (2021). Recognition of Korean Alphabet (Hangul) Handwriting into Latin Characters Using Backpropagation Method. International Journal of Artificial Intelligence & Robotics (IJAIR), 3(2), 50-57. https://doi.org/10.25139/ijair.v3i2.4210
Issue
Vol. 3 No. 2 (2021): November 2021
Section
Articles

Copyright (c) 2021 Anang Aris Widodo, Muchammad Yuska Izza Mahendra, Mohammad Zoqi Sarwani

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