Newspaper document analysis featuring connected line segmentation

Phillip E. Mitchell; Hong Yan

doi:10.1109/ICDAR.2001.953971

Newspaper document analysis featuring connected line segmentation

Phillip E. Mitchell
, Hong Yan

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

23 Citations (Scopus)

Abstract

This paper presents an algorithm designed to segment and classify newspaper documents. A notable feature of this algorithm is the ability to detect lines in the document - including lines that are connected to other components. A bottom-up approach is used to segment the image into patterns, and then each pattern is classified into one of seven types. Complete regions are then formed from the classified patterns.

Original language	English
Title of host publication	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
Publisher	IEEE Computer Society
Pages	1181-1185
Volume	2001-January
ISBN (Print)	0769512631
DOIs	https://doi.org/10.1109/ICDAR.2001.953971
Publication status	Published - 2001
Event	6th International Conference on Document Analysis and Recognition, ICDAR 2001 - Seattle, United States Duration: 10 Sept 2001 → 13 Sept 2001

Publication series

Name
Volume	2001-January
ISSN (Print)	1520-5363

Conference

Conference	6th International Conference on Document Analysis and Recognition, ICDAR 2001
Place	United States
City	Seattle
Period	10/09/01 → 13/09/01

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10.1109/ICDAR.2001.953971

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title = "Newspaper document analysis featuring connected line segmentation",

abstract = "This paper presents an algorithm designed to segment and classify newspaper documents. A notable feature of this algorithm is the ability to detect lines in the document - including lines that are connected to other components. A bottom-up approach is used to segment the image into patterns, and then each pattern is classified into one of seven types. Complete regions are then formed from the classified patterns.",

author = "Mitchell, \{Phillip E.\} and Hong Yan",

year = "2001",

doi = "10.1109/ICDAR.2001.953971",

language = "English",

isbn = "0769512631",

volume = "2001-January",

publisher = "IEEE Computer Society",

pages = "1181--1185",

booktitle = "Proceedings of the International Conference on Document Analysis and Recognition, ICDAR",

address = "United States",

note = "6th International Conference on Document Analysis and Recognition, ICDAR 2001 ; Conference date: 10-09-2001 Through 13-09-2001",

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Mitchell, PE & Yan, H 2001, Newspaper document analysis featuring connected line segmentation. in Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. vol. 2001-January, 953971, IEEE Computer Society, pp. 1181-1185, 6th International Conference on Document Analysis and Recognition, ICDAR 2001, Seattle, United States, 10/09/01. https://doi.org/10.1109/ICDAR.2001.953971

Newspaper document analysis featuring connected line segmentation. / Mitchell, Phillip E.; Yan, Hong.
Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. Vol. 2001-January IEEE Computer Society, 2001. p. 1181-1185 953971.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

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AU - Yan, Hong

PY - 2001

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N2 - This paper presents an algorithm designed to segment and classify newspaper documents. A notable feature of this algorithm is the ability to detect lines in the document - including lines that are connected to other components. A bottom-up approach is used to segment the image into patterns, and then each pattern is classified into one of seven types. Complete regions are then formed from the classified patterns.

AB - This paper presents an algorithm designed to segment and classify newspaper documents. A notable feature of this algorithm is the ability to detect lines in the document - including lines that are connected to other components. A bottom-up approach is used to segment the image into patterns, and then each pattern is classified into one of seven types. Complete regions are then formed from the classified patterns.

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U2 - 10.1109/ICDAR.2001.953971

DO - 10.1109/ICDAR.2001.953971

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0769512631

VL - 2001-January

SP - 1181

EP - 1185

BT - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

PB - IEEE Computer Society

T2 - 6th International Conference on Document Analysis and Recognition, ICDAR 2001

Y2 - 10 September 2001 through 13 September 2001

ER -

Newspaper document analysis featuring connected line segmentation

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