Table structure recognition based on robust block segmentation

Thomas G. Kieninger

doi:10.1117/12.304642

1 April 1998 Table structure recognition based on robust block segmentation

Thomas G. Kieninger

Proceedings Volume 3305, Document Recognition V; (1998) https://doi.org/10.1117/12.304642
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

This paper presents an efficient approach to identify tabular structures within either electronic or paper documents. The resulting T-Recs system takes word bounding box information as input, and outputs the corresponding logical text block units. Starting with an arbitrary word as block seed the algorithm recursively expands this block to all words that interleave with their vertical neighbors. Since even smallest gaps of table columns prevent their words from mutual interleaving, this initial segmentation is able to identify and isolate such columns. In order to deal with some inherent segmentation errors caused by isolated lines, overhanging words, or cells spawning more than one column, a series of postprocessing steps is added. These steps benefit form a very simple distinction between type 1 and type 2 blocks: type 1 blocks are those of at most one word per line, all others are of type 2. This distinction allows the selective application of heuristics to each group of blocks. The conjoint decomposition of column blocks into subsets of table cells leads to the final block segmentation of a homogeneous abstraction level. These segments serve the final layout analysis which identifies table environments and cells that are stretching over several rows and/or columns.

Citation Download Citation

Thomas G. Kieninger "Table structure recognition based on robust block segmentation", Proc. SPIE 3305, Document Recognition V, (1 April 1998); https://doi.org/10.1117/12.304642

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available