Newspaper document analysis featuring connected line segmentation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the International Conference on Document Analysis and Recognition, ICDAR
PublisherIEEE Computer Society
Pages1181-1185
Volume2001-January
ISBN (Print)0769512631
Publication statusPublished - 2001

Publication series

Name
Volume2001-January
ISSN (Print)1520-5363

Conference

Title6th International Conference on Document Analysis and Recognition, ICDAR 2001
PlaceUnited States
CitySeattle
Period10 - 13 September 2001

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.

Citation Format(s)

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: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review