research-article

Table detection in heterogeneous documents

Authors:

Faisal Shafait,

Ray SmithAuthors Info & Claims

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

Pages 65 - 72

https://doi.org/10.1145/1815330.1815339

Published: 09 June 2010 Publication History

Abstract

Detecting tables in document images is important since not only do tables contain important information, but also most of the layout analysis methods fail in the presence of tables in the document image. Existing approaches for table detection mainly focus on detecting tables in single columns of text and do not work reliably on documents with varying layouts. This paper presents a practical algorithm for table detection that works with a high accuracy on documents with varying layouts (company reports, newspaper articles, magazine pages, ...). An open source implementation of the algorithm is provided as part of the Tesseract OCR engine. Evaluation of the algorithm on document images from publicly available UNLV dataset shows competitive performance in comparison to the table detection module of a commercial OCR system.

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Cited By

Salaheldin Kasem MAbdallah ABerendeyev AElkady EMahmoud MAbdalla MHamada MVascon SNurseitov DTaj-Eddin I(2024)Deep Learning for Table Detection and Structure Recognition: A SurveyACM Computing Surveys10.1145/365728156:12(1-41)Online publication date: 10-Apr-2024
https://dl.acm.org/doi/10.1145/3657281
Saout TLardeux FSaubion F(2024)An Overview of Data Extraction From InvoicesIEEE Access10.1109/ACCESS.2024.336052812(19872-19886)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3360528
Kawoosa HKanroo MRana KGoyal P(2024)Robust page object detection network for heterogeneous document imagesInternational Journal on Document Analysis and Recognition (IJDAR)10.1007/s10032-024-00498-3Online publication date: 16-Aug-2024
https://doi.org/10.1007/s10032-024-00498-3
Show More Cited By

Index Terms

Table detection in heterogeneous documents
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Document analysis

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Abstract
Table detection is a crucial step in several document analysis applications as tables are used to present essential information to the reader in a structured manner. In companies that deal with a large amount of data, administrative documents must ...

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cover image ACM Other conferences

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

June 2010

490 pages

ISBN:9781605587738

DOI:10.1145/1815330

General Chairs:
David Doermann
University of Maryland, College Park
,
Venu Govindaraju
University at Buffalo, SUNY
,
Daniel Lopresti
Lehigh University
,
Prem Natarajan
Raytheon BBN Technologies

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 09 June 2010

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DAS '10

DAS '10: The Eighth IAPR International Workshop on Document Analysis Systems

June 9 - 11, 2010

Massachusetts, Boston, USA

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Cited By

Salaheldin Kasem MAbdallah ABerendeyev AElkady EMahmoud MAbdalla MHamada MVascon SNurseitov DTaj-Eddin I(2024)Deep Learning for Table Detection and Structure Recognition: A SurveyACM Computing Surveys10.1145/365728156:12(1-41)Online publication date: 10-Apr-2024
https://dl.acm.org/doi/10.1145/3657281
Saout TLardeux FSaubion F(2024)An Overview of Data Extraction From InvoicesIEEE Access10.1109/ACCESS.2024.336052812(19872-19886)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3360528
Kawoosa HKanroo MRana KGoyal P(2024)Robust page object detection network for heterogeneous document imagesInternational Journal on Document Analysis and Recognition (IJDAR)10.1007/s10032-024-00498-3Online publication date: 16-Aug-2024
https://doi.org/10.1007/s10032-024-00498-3
Saout TLardeux FSaubion F(2023)A Two-stage Approach for Tables Extraction in Invoices2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI)10.1109/ICTAI59109.2023.00010(10-15)Online publication date: 6-Nov-2023
https://doi.org/10.1109/ICTAI59109.2023.00010
Bhowmik SBhowmik S(2023)Document Region SegmentationDocument Layout Analysis10.1007/978-981-99-4277-0_3(31-42)Online publication date: 1-Aug-2023
https://doi.org/10.1007/978-981-99-4277-0_3
Madake JPandey S(2023)Tabular Data Extraction From DocumentsProceedings of International Conference on Recent Trends in Computing10.1007/978-981-19-8825-7_37(429-439)Online publication date: 21-Mar-2023
https://doi.org/10.1007/978-981-19-8825-7_37
Kallempudi GHashmi KPagani ALiwicki MStricker DAfzal M(2022)Toward Semi-Supervised Graphical Object Detection in Document ImagesFuture Internet10.3390/fi1406017614:6(176)Online publication date: 8-Jun-2022
https://doi.org/10.3390/fi14060176
Arlazarov VAndreeva EBulatov KNikolaev DPetrova OSavelev BSlavin O(2022)Document image analysis and recognition: a surveyComputer Optics10.18287/2412-6179-CO-102046:4(567-589)Online publication date: Aug-2022
https://doi.org/10.18287/2412-6179-CO-1020
Xue XWu JZhang J(2022)Semiautomated Generation of Logic Rules for Tabular Information in Building Codes to Support Automated Code Compliance CheckingJournal of Computing in Civil Engineering10.1061/(ASCE)CP.1943-5487.000100036:1Online publication date: Jan-2022
https://doi.org/10.1061/(ASCE)CP.1943-5487.0001000
Ou EKim MLoh PAllen TAgasie RLiu K(2022)Automatic recognition system for document digitization in nuclear power plantsNuclear Engineering and Design10.1016/j.nucengdes.2022.111975398(111975)Online publication date: Nov-2022
https://doi.org/10.1016/j.nucengdes.2022.111975
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