Abstract
In recent years, the need to exploit digitized document data has been increasing. In this paper, we address the problem of parsing digitized Vietnamese paper documents. The digitized Vietnamese documents are mainly in the form of scanned images with diverse layouts and special characters introducing many challenges. To this end, we first collect the UIT-DODV dataset, a novel Vietnamese document image dataset that includes scientific papers in Vietnamese derived from different scientific conferences. We compile both images that were converted from PDF and scanned by a smartphone in addition a physical scanner that poses many new challenges. Additionally, we further leverage the state-of-the-art object detector along with the fused loss function to efficiently parse the Vietnamese paper documents. Extensive experiments conducted on the UIT-DODV dataset provide a comprehensive evaluation and insightful analysis.
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UIT-DODV published at https://uit-together.github.io/datasets/.
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Acknowledgment
The research team would like to express our sincere thanks to the Multimedia Communications Laboratory (MMLab) - University of Information Technology, VNU-HCM for supporting this research. We want to thank Can Tho University Journal of Science for the assistance in the data collection. This project is partially funded under National Science Foundation (NSF) under Grant No. 2025234 and Vietnam National University Ho Chi Minh City (VNU-HCM) under grant number DSC2021-26-03.
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Dieu, L.T., Nguyen, T.T., Vo, N.D., Nguyen, T.V., Nguyen, K. (2021). Parsing Digitized Vietnamese Paper Documents. In: Tsapatsoulis, N., Panayides, A., Theocharides, T., Lanitis, A., Pattichis, C., Vento, M. (eds) Computer Analysis of Images and Patterns. CAIP 2021. Lecture Notes in Computer Science(), vol 13052. Springer, Cham. https://doi.org/10.1007/978-3-030-89128-2_37
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