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

Widodo, Anang Aris and Izza Mahendra, Muchammad Yuska and Sarwani, Mohammad Zoqi (2021) Recognition of Korean Alphabet (Hangul) Handwriting into Latin Characters Using Backpropagation Method. International Journal of Artificial Intelligence & Robotics (IJAIR), 3 (2). pp. 50-56. ISSN 2686-6269

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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).

Item Type: Article
Uncontrolled Keywords: Korea, Hangul, Backpropagation Method, Artificial Neural Network
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Teknologi Informasi > Informatika
Depositing User: Anang Aris Widodo
Date Deposited: 05 Apr 2023 02:51
Last Modified: 05 Apr 2023 02:51
URI: http://repository.unmerpas.ac.id/id/eprint/171

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