Developing an OCR model for Extracting Information from Invoices with Korean Language

Abstract:Invoices are commercial documents that contain various pieces of information, including the purchased items, time, and total money. Making the extraction of important information crucial. The stored information serves different purposes. Korean language is the native language of about 80 million people, playing an important role in not only South and North Korea but also in many other countries such as Vietnam, Philippine where a large number of Korean companies are located. In this context, to automatically extract proper information from the invoices with Korean language, we propose an efficient Optical Character Recognition (OCR) model in which a deep learning model is combined with some image preprocessing techniques. The proposed OCR model is assessed in a rich set of collected invoices showing that 87% F1-score can be achieved with negligible time processing.

Computation and Language (cs.CL)

arXiv:2609.35796 [cs.CL]

(or arXiv:2609.35796v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.35796 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

https://doi.org/10.1109/ATC58710.2023.10318877 Focus to learn more DOI(s) linking to related resources

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