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http://dx.doi.org/10.9717/kmms.2022.25.5.695

Structure Recognition Method in Various Table Types for Document Processing Automation  

Lee, Dong-Seok (AI Grand ICT Research Center, Dong-Eui University)
Kwon, Soon-Kak (Dept. of Computer Software Engineering, Dongeui University)
Publication Information
Journal of Korea Multimedia Society / v.25, no.5, 2022 , pp. 695-702 More about this Journal
Abstract
In this paper, we propose the method of a table structure recognition in various table types for document processing automation. A table with items surrounded by ruled lines are analyzed by detecting horizontal and vertical lines for recognizing the table structure. In case of a table with items separated by spaces, the table structure are recognized by analyzing the arrangement of row items. After recognizing the table structure, the areas of the table items are input into OCR engine and the character recognition result output to a text file in a structured format such as CSV or JSON. In simulation results, the average accuracy of table item recognition is about 94%.
Keywords
Table structure detection; Document processing automation; Optical character recognition;
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