An application of Vietnamese handwriting text recognition for information extraction from high school admission form

Pham The Bao, Le Tran Anh Dang, Nguyen Duy Tam, Nguyen Nhat Truong, Pham Cung Le Thien Vu, Trinh Tan Dat


This paper presents an effective Vietnamese handwritten text recognition model by applying an improved convolutional recurrent neural networks (CRNNs) model to high school enrollment forms in Tay Ninh province, Vietnam. First, the proposed model extracts data areas containing text characters from forms. Then, we connect text boxes on the same row and divide the fields that containing text into three specific regions. Finally, we detect areas containing text characters for handwritten text recognition. We use word error rate (WER) to evaluate the recognition process and obtain a result of 0.3602. This result is one of the best solutions to the Vietnamese handwritten text recognition problem.


Attention; Convolutional neural networks; Handwriting; Long short-term memory; Recognition; Vietnamese

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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