Text line detection in corrupted and damaged historical manuscripts

Irina Rabaev; Ofer Biller; Jihad El-Sana; Klara Kedem; Itshak Dinstein

doi:10.1109/ICDAR.2013.166

Text line detection in corrupted and damaged historical manuscripts

Irina Rabaev, Ofer Biller, Jihad El-Sana, Klara Kedem, Itshak Dinstein

Research output: Contribution to journal › Conference article › peer-review

12 Scopus citations

Abstract

Most of the algorithms proposed for text line detection are designed to process binary images as input. For severely degraded documents, binarization often introduces significant noise and other artifacts. In this work we present a novel method designed to detect text lines directly in gray scale images. The method consists of two stages. Potential characters are detected in the first stage. This is done by analyzing the evolution maps of connected components obtained by a sliding threshold. The detected potential characters are grouped into text lines in the second stage using sweep-line approach. The suggested method is especially powerful when applied to torn and damaged documents that other algorithms are not able to deal with.

Original language	English
Article number	6628731
Pages (from-to)	812-816
Number of pages	5
Journal	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
DOIs	https://doi.org/10.1109/ICDAR.2013.166
State	Published - 11 Dec 2013
Event	12th International Conference on Document Analysis and Recognition, ICDAR 2013 - Washington, DC, United States Duration: 25 Aug 2013 → 28 Aug 2013

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

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10.1109/ICDAR.2013.166

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title = "Text line detection in corrupted and damaged historical manuscripts",

abstract = "Most of the algorithms proposed for text line detection are designed to process binary images as input. For severely degraded documents, binarization often introduces significant noise and other artifacts. In this work we present a novel method designed to detect text lines directly in gray scale images. The method consists of two stages. Potential characters are detected in the first stage. This is done by analyzing the evolution maps of connected components obtained by a sliding threshold. The detected potential characters are grouped into text lines in the second stage using sweep-line approach. The suggested method is especially powerful when applied to torn and damaged documents that other algorithms are not able to deal with.",

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T1 - Text line detection in corrupted and damaged historical manuscripts

AU - Rabaev, Irina

AU - Biller, Ofer

AU - El-Sana, Jihad

AU - Kedem, Klara

AU - Dinstein, Itshak

PY - 2013/12/11

Y1 - 2013/12/11

N2 - Most of the algorithms proposed for text line detection are designed to process binary images as input. For severely degraded documents, binarization often introduces significant noise and other artifacts. In this work we present a novel method designed to detect text lines directly in gray scale images. The method consists of two stages. Potential characters are detected in the first stage. This is done by analyzing the evolution maps of connected components obtained by a sliding threshold. The detected potential characters are grouped into text lines in the second stage using sweep-line approach. The suggested method is especially powerful when applied to torn and damaged documents that other algorithms are not able to deal with.

AB - Most of the algorithms proposed for text line detection are designed to process binary images as input. For severely degraded documents, binarization often introduces significant noise and other artifacts. In this work we present a novel method designed to detect text lines directly in gray scale images. The method consists of two stages. Potential characters are detected in the first stage. This is done by analyzing the evolution maps of connected components obtained by a sliding threshold. The detected potential characters are grouped into text lines in the second stage using sweep-line approach. The suggested method is especially powerful when applied to torn and damaged documents that other algorithms are not able to deal with.

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DO - 10.1109/ICDAR.2013.166

M3 - Conference article

AN - SCOPUS:84889574831

SN - 1520-5363

SP - 812

EP - 816

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

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

M1 - 6628731

T2 - 12th International Conference on Document Analysis and Recognition, ICDAR 2013

Y2 - 25 August 2013 through 28 August 2013

ER -

Text line detection in corrupted and damaged historical manuscripts

Abstract

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