Developing an OCR model for Extracting Information from Invoices with Korean Language
Developing an OCR model for Extracting Information from Invoices with Korean Language
开发用于提取韩语发票信息的 OCR 模型
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.
摘要： 发票是包含各种信息的商业单据，其中包括所购商品、时间以及总金额。因此，提取这些重要信息至关重要，且所存储的信息具有多种用途。
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.
韩语是约 8000 万人的母语，不仅在朝鲜和韩国发挥着重要作用，在越南、菲律宾等拥有大量韩资企业的国家也同样重要。
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.
在此背景下，为了从韩语发票中自动提取准确信息，我们提出了一种高效的光学字符识别（OCR）模型，该模型将深度学习模型与多种图像预处理技术相结合。
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.
该 OCR 模型通过一组丰富的发票数据集进行了评估，结果显示其 F1 分数可达到 87%，且处理时间几乎可以忽略不计。
Paper Details:
- Authors: Xiem HoangVan, Phu TranQuang, Minh DinhBao, Tien VuHuu
- arXiv ID: 2609.35796
- Subject: Computation and Language (cs.CL)
- Submission Date: 17 Sep 2026
论文详情：
- 作者： Xiem HoangVan, Phu TranQuang, Minh DinhBao, Tien VuHuu
- arXiv ID： 2609.35796
- 学科： 计算与语言 (cs.CL)
- 提交日期： 2026 年 9 月 17 日