- P-ISSN1738-6764
- E-ISSN2093-7504
- KCI
ISSN : 1738-6764
Table Detection from Document Image using Vertical Arrangement of Text Blocks
Tran, Tuan Anh
Oh, Aran
Kim, Soo Hyung
Na, In Seop
Abstract
Table detection is a challenging problem and plays an important role in document layout analysis. In this paper, we propose an effective method to identify the table region from document images. First, the regions of interest (ROIs) are recognized as the table candidates. In each ROI, we locate text components and extract text blocks. After that, we check all text blocks to determine if they are arranged horizontally or vertically and compare the height of each text block with the average height. If the text blocks satisfy a series of rules, the ROI is regarded as a table. Experiments on the ICDAR 2013 dataset show that the results obtained are very encouraging. This proves the effectiveness and superiority of our proposed method.
- keywords
- Table Detection, Text Block, Expanding ROI, Vertical Arrangement
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