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http://dx.doi.org/10.5392/IJoC.2015.11.4.077

Table Detection from Document Image using Vertical Arrangement of Text Blocks  

Tran, Dieu Ni (School of Electronics and Computer Engineering Chonnam National University)
Tran, Tuan Anh (School of Electronics and Computer Engineering Chonnam National University)
Oh, Aran (School of Electronics and Computer Engineering Chonnam National University)
Kim, Soo Hyung (School of Electronics and Computer Engineering Chonnam National University)
Na, In Seop (School of Electronics and Computer Engineering Chonnam National University)
Publication Information
International Journal of Contents / v.11, no.4, 2015 , pp. 77-85 More about this Journal
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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