Robust Detection of Tables in Documents Using Scores from Table Cell Cores Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.1007/s42979-022-01041-z
Table detection is an essential step in many document analysis systems. Tabular data are a pivotal form of information representation that can organize data in a conventional structure for comfortable and quick information retrieval and comparison. Detection of table structures in PDF files or images is a challenging task because of the variability of table layouts, and sometimes the tabular structures’ similarities with non-tabular elements like charts, plots, etc. In this work, we have presented a table detection method using a geometric analysis of the table cell cores that represents the table cell texts. The proposed method works by analyzing the text gap information, and hence it can detect the table cell cores, irrespective of the presence of the table boundary lines and cell-separating rule-lines. Experimentations have been done on various document images of complex structures from well-known datasets. The detection accuracies obtained by us corroborate the usefulness of the proposed method.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s42979-022-01041-z
- https://link.springer.com/content/pdf/10.1007/s42979-022-01041-z.pdf
- OA Status
- hybrid
- Cited By
- 4
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4211029414
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4211029414Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s42979-022-01041-zDigital Object Identifier
- Title
-
Robust Detection of Tables in Documents Using Scores from Table Cell CoresWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-02-12Full publication date if available
- Authors
-
Md. Ajij, Sanjoy Pratihar, Diptendu Sinha Roy, Thomas HanneList of authors in order
- Landing page
-
https://doi.org/10.1007/s42979-022-01041-zPublisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s42979-022-01041-z.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1007/s42979-022-01041-z.pdfDirect OA link when available
- Concepts
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Table (database), Computer science, Representation (politics), Data mining, Information retrieval, Task (project management), Boundary (topology), Pattern recognition (psychology), Artificial intelligence, Mathematics, Engineering, Political science, Systems engineering, Law, Mathematical analysis, PoliticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2023: 1, 2022: 2Per-year citation counts (last 5 years)
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29Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5068471666 |
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| corresponding_institution_ids | https://openalex.org/I2972652528 |
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