Logical labeling of document images using layout graph matching with adaptive learning

Jian Liang; David Doermann

doi:10.1007/3-540-45869-7_26

Logical labeling of document images using layout graph matching with adaptive learning

Jian Liang
, David Doermann

Department of Computer Science and Engineering

University of Maryland, College Park

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 Scopus citations

Abstract

Logical structure analysis of document images is an important problem in document image understanding. In this paper, we propose a graph matching approach to label logical components on a document page. Our system is able to learn a model for a document class, use this model to label document images through graph matching, and adaptively improve the model with error feed back. We tested our method on journal/proceeding article title pages. The experimental results show promising accuracy, and confirm the ability of adaptive learning.

Original language	English
Title of host publication	Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings
Editors	Daniel Lopresti, Jianying Hu, Ramanujan Kashi
Publisher	Springer Verlag
Pages	224-235
Number of pages	12
ISBN (Print)	3540440682, 9783540440680
DOIs	https://doi.org/10.1007/3-540-45869-7_26
State	Published - 2002
Event	5th International Workshop on Document Analysis Systems, DAS 2002 - Princeton, United States Duration: Aug 19 2002 → Aug 21 2002

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2423
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Workshop on Document Analysis Systems, DAS 2002
Country/Territory	United States
City	Princeton
Period	08/19/02 → 08/21/02

Access to Document

10.1007/3-540-45869-7_26

Cite this

Liang, J., & Doermann, D. (2002). Logical labeling of document images using layout graph matching with adaptive learning. In D. Lopresti, J. Hu, & R. Kashi (Eds.), Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings (pp. 224-235). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2423). Springer Verlag. https://doi.org/10.1007/3-540-45869-7_26

Liang, Jian ; Doermann, David. / Logical labeling of document images using layout graph matching with adaptive learning. Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. editor / Daniel Lopresti ; Jianying Hu ; Ramanujan Kashi. Springer Verlag, 2002. pp. 224-235 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{f1887ec1acac40768e81f339af49661b,

title = "Logical labeling of document images using layout graph matching with adaptive learning",

abstract = "Logical structure analysis of document images is an important problem in document image understanding. In this paper, we propose a graph matching approach to label logical components on a document page. Our system is able to learn a model for a document class, use this model to label document images through graph matching, and adaptively improve the model with error feed back. We tested our method on journal/proceeding article title pages. The experimental results show promising accuracy, and confirm the ability of adaptive learning.",

author = "Jian Liang and David Doermann",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002.; 5th International Workshop on Document Analysis Systems, DAS 2002 ; Conference date: 19-08-2002 Through 21-08-2002",

year = "2002",

doi = "10.1007/3-540-45869-7\_26",

language = "English",

isbn = "3540440682",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "224--235",

editor = "Daniel Lopresti and Jianying Hu and Ramanujan Kashi",

booktitle = "Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings",

address = "Germany",

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Liang, J & Doermann, D 2002, Logical labeling of document images using layout graph matching with adaptive learning. in D Lopresti, J Hu & R Kashi (eds), Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2423, Springer Verlag, pp. 224-235, 5th International Workshop on Document Analysis Systems, DAS 2002, Princeton, United States, 08/19/02. https://doi.org/10.1007/3-540-45869-7_26

Logical labeling of document images using layout graph matching with adaptive learning. / Liang, Jian; Doermann, David.
Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. ed. / Daniel Lopresti; Jianying Hu; Ramanujan Kashi. Springer Verlag, 2002. p. 224-235 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2423).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Logical structure analysis of document images is an important problem in document image understanding. In this paper, we propose a graph matching approach to label logical components on a document page. Our system is able to learn a model for a document class, use this model to label document images through graph matching, and adaptively improve the model with error feed back. We tested our method on journal/proceeding article title pages. The experimental results show promising accuracy, and confirm the ability of adaptive learning.

AB - Logical structure analysis of document images is an important problem in document image understanding. In this paper, we propose a graph matching approach to label logical components on a document page. Our system is able to learn a model for a document class, use this model to label document images through graph matching, and adaptively improve the model with error feed back. We tested our method on journal/proceeding article title pages. The experimental results show promising accuracy, and confirm the ability of adaptive learning.

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Liang J, Doermann D. Logical labeling of document images using layout graph matching with adaptive learning. In Lopresti D, Hu J, Kashi R, editors, Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. Springer Verlag. 2002. p. 224-235. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45869-7_26

Logical labeling of document images using layout graph matching with adaptive learning

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