Document page segmentation by integrating distributed soft decisions

Kamran Etemad; Rama Chellappa; David Doermann

doi:10.1109/icnn.1994.374857

Document page segmentation by integrating distributed soft decisions

Kamran Etemad
, Rama Chellappa
, 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

5 Scopus citations

Abstract

A new algorithm for image segmentation is suggested. The suggested algorithm is based on making local soft decisions on small blocks and integrating them to reduce their `ambiguities' and increase their `confidence' as more contextual evidence is obtained from the image data. Integration is performed by vote propagation across windows (within and across scales) using majorities of weighted votes. The algorithm has been tested on some document page decomposition tasks; the results of these tests are presented. This method is based on parallel, distributed and independent computations and has low complexity. It is general and can be applied to different segmentation and classification tasks.

Original language	English
Title of host publication	IEEE International Conference on Neural Networks - Conference Proceedings
Publisher	IEEE
Pages	4022-4027
Number of pages	6
ISBN (Print)	078031901X
DOIs	https://doi.org/10.1109/icnn.1994.374857
State	Published - 1994
Event	Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA Duration: Jun 27 1994 → Jun 29 1994

Publication series

Name	IEEE International Conference on Neural Networks - Conference Proceedings
Volume	6

Conference

Conference	Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
City	Orlando, FL, USA
Period	06/27/94 → 06/29/94

Access to Document

10.1109/icnn.1994.374857

Cite this

@inproceedings{5c78b497e2e04583a31288a73bec80a7,

title = "Document page segmentation by integrating distributed soft decisions",

abstract = "A new algorithm for image segmentation is suggested. The suggested algorithm is based on making local soft decisions on small blocks and integrating them to reduce their `ambiguities' and increase their `confidence' as more contextual evidence is obtained from the image data. Integration is performed by vote propagation across windows (within and across scales) using majorities of weighted votes. The algorithm has been tested on some document page decomposition tasks; the results of these tests are presented. This method is based on parallel, distributed and independent computations and has low complexity. It is general and can be applied to different segmentation and classification tasks.",

author = "Kamran Etemad and Rama Chellappa and David Doermann",

year = "1994",

doi = "10.1109/icnn.1994.374857",

language = "English",

isbn = "078031901X",

series = "IEEE International Conference on Neural Networks - Conference Proceedings",

publisher = "IEEE",

pages = "4022--4027",

booktitle = "IEEE International Conference on Neural Networks - Conference Proceedings",

note = "Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) ; Conference date: 27-06-1994 Through 29-06-1994",

}

Etemad, K, Chellappa, R & Doermann, D 1994, Document page segmentation by integrating distributed soft decisions. in IEEE International Conference on Neural Networks - Conference Proceedings. IEEE International Conference on Neural Networks - Conference Proceedings, vol. 6, IEEE, pp. 4022-4027, Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), Orlando, FL, USA, 06/27/94. https://doi.org/10.1109/icnn.1994.374857

Document page segmentation by integrating distributed soft decisions. / Etemad, Kamran; Chellappa, Rama; Doermann, David.
IEEE International Conference on Neural Networks - Conference Proceedings. IEEE, 1994. p. 4022-4027 (IEEE International Conference on Neural Networks - Conference Proceedings; Vol. 6).

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

TY - GEN

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AU - Chellappa, Rama

AU - Doermann, David

PY - 1994

Y1 - 1994

N2 - A new algorithm for image segmentation is suggested. The suggested algorithm is based on making local soft decisions on small blocks and integrating them to reduce their `ambiguities' and increase their `confidence' as more contextual evidence is obtained from the image data. Integration is performed by vote propagation across windows (within and across scales) using majorities of weighted votes. The algorithm has been tested on some document page decomposition tasks; the results of these tests are presented. This method is based on parallel, distributed and independent computations and has low complexity. It is general and can be applied to different segmentation and classification tasks.

AB - A new algorithm for image segmentation is suggested. The suggested algorithm is based on making local soft decisions on small blocks and integrating them to reduce their `ambiguities' and increase their `confidence' as more contextual evidence is obtained from the image data. Integration is performed by vote propagation across windows (within and across scales) using majorities of weighted votes. The algorithm has been tested on some document page decomposition tasks; the results of these tests are presented. This method is based on parallel, distributed and independent computations and has low complexity. It is general and can be applied to different segmentation and classification tasks.

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DO - 10.1109/icnn.1994.374857

M3 - Conference contribution

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SN - 078031901X

T3 - IEEE International Conference on Neural Networks - Conference Proceedings

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BT - IEEE International Conference on Neural Networks - Conference Proceedings

PB - IEEE

T2 - Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)

Y2 - 27 June 1994 through 29 June 1994

ER -

Document page segmentation by integrating distributed soft decisions

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