THAIWRITTENNET: THAI HANDWRITTEN SCRIPT RECOGNITION USING DEEP NEURAL NETWORKS

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Volume 3 (1), June 2020, Pages 75-93

Pakpoom Mookdarsanit, Lawankorn Mookdarsanit

Chandrakasem Rajabhat University, Bangkok, Thailand, This email address is being protected from spambots. You need JavaScript enabled to view it., This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Thai is a non-tonal language usage for 70 million speakers in Thailand. A variety of Thai handwrit-ten styles has been a challenge in handwriting recognition. In this paper, we propose a novel “ThaiWrittenNet” based on Convolutional Neural Network (ConvNet or CNN) with a cutout to identify the handwritten recognitions. Deep Belief Network (DBN) is also combined with Con-vNet to reduce network complexity. From the results, ThaiWrittenNet outperforms the flat Con-vNet and other handcrafted features with traditional machine learning algorithms. It appears that DBN helps ConvNet to improve the accuracy of Thai-handwritten recognition.

Keywords:

Handwriting recognition, Convolutional neural network, Deep belief network, Thai handwriting recognition

DOI: https://doi.org/10.32010/26166127.2020.3.1.75.93

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