Structural features by MCR expression for printed Arabic character recognition

A. B.C. Zidouri; S. Chinveeraphan; M. Sato

doi:10.1007/3-540-60298-4_314

Structural features by MCR expression for printed Arabic character recognition

A. B.C. Zidouri
, S. Chinveeraphan
, M. Sato

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

2 Scopus citations

Abstract

This paper discribes how stroke features in document images are extracted and used for the recognition of printed Arabic characters. It is of importance to provide a good base representation that facilitate analysis and processing of document images. The strokes are extracted by a method called Minimum Covering Runs (MCR)[1]. This method of representing binary images by a minimum number of horizontal and vertical runs is used as a preprocessing step. The strokes are labeled and ordered, a feature space for the 100 shapes of the 28 Arabic characters is build. The system is under developement but the recognition rate obtained at this stage, 95.5% is encouraging.

Original language	English
Title of host publication	Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings
Editors	Carlo Braccini, Leila DeFloriani, Gianni Vernazza
Publisher	Springer Verlag
Pages	557-562
Number of pages	6
ISBN (Print)	3540602984, 9783540602989
DOIs	https://doi.org/10.1007/3-540-60298-4_314
State	Published - 1995
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	974
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1995.

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/3-540-60298-4_314

Cite this

Zidouri, A. B. C., Chinveeraphan, S., & Sato, M. (1995). Structural features by MCR expression for printed Arabic character recognition. In C. Braccini, L. DeFloriani, & G. Vernazza (Eds.), Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings (pp. 557-562). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 974). Springer Verlag. https://doi.org/10.1007/3-540-60298-4_314

Zidouri, A. B.C. ; Chinveeraphan, S. ; Sato, M. / Structural features by MCR expression for printed Arabic character recognition. Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings. editor / Carlo Braccini ; Leila DeFloriani ; Gianni Vernazza. Springer Verlag, 1995. pp. 557-562 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{893770f85c564354a98b8a3bd74c1f58,

title = "Structural features by MCR expression for printed Arabic character recognition",

abstract = "This paper discribes how stroke features in document images are extracted and used for the recognition of printed Arabic characters. It is of importance to provide a good base representation that facilitate analysis and processing of document images. The strokes are extracted by a method called Minimum Covering Runs (MCR)[1]. This method of representing binary images by a minimum number of horizontal and vertical runs is used as a preprocessing step. The strokes are labeled and ordered, a feature space for the 100 shapes of the 28 Arabic characters is build. The system is under developement but the recognition rate obtained at this stage, 95.5\% is encouraging.",

author = "Zidouri, \{A. B.C.\} and S. Chinveeraphan and M. Sato",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1995.",

year = "1995",

doi = "10.1007/3-540-60298-4\_314",

language = "English",

isbn = "3540602984",

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

publisher = "Springer Verlag",

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editor = "Carlo Braccini and Leila DeFloriani and Gianni Vernazza",

booktitle = "Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings",

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}

Zidouri, ABC, Chinveeraphan, S & Sato, M 1995, Structural features by MCR expression for printed Arabic character recognition. in C Braccini, L DeFloriani & G Vernazza (eds), Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 974, Springer Verlag, pp. 557-562. https://doi.org/10.1007/3-540-60298-4_314

Structural features by MCR expression for printed Arabic character recognition. / Zidouri, A. B.C.; Chinveeraphan, S.; Sato, M.
Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings. ed. / Carlo Braccini; Leila DeFloriani; Gianni Vernazza. Springer Verlag, 1995. p. 557-562 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 974).

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

TY - GEN

T1 - Structural features by MCR expression for printed Arabic character recognition

AU - Zidouri, A. B.C.

AU - Chinveeraphan, S.

AU - Sato, M.

PY - 1995

Y1 - 1995

N2 - This paper discribes how stroke features in document images are extracted and used for the recognition of printed Arabic characters. It is of importance to provide a good base representation that facilitate analysis and processing of document images. The strokes are extracted by a method called Minimum Covering Runs (MCR)[1]. This method of representing binary images by a minimum number of horizontal and vertical runs is used as a preprocessing step. The strokes are labeled and ordered, a feature space for the 100 shapes of the 28 Arabic characters is build. The system is under developement but the recognition rate obtained at this stage, 95.5% is encouraging.

AB - This paper discribes how stroke features in document images are extracted and used for the recognition of printed Arabic characters. It is of importance to provide a good base representation that facilitate analysis and processing of document images. The strokes are extracted by a method called Minimum Covering Runs (MCR)[1]. This method of representing binary images by a minimum number of horizontal and vertical runs is used as a preprocessing step. The strokes are labeled and ordered, a feature space for the 100 shapes of the 28 Arabic characters is build. The system is under developement but the recognition rate obtained at this stage, 95.5% is encouraging.

UR - https://www.scopus.com/pages/publications/84947709017

U2 - 10.1007/3-540-60298-4_314

DO - 10.1007/3-540-60298-4_314

M3 - Conference contribution

AN - SCOPUS:84947709017

SN - 3540602984

SN - 9783540602989

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 557

EP - 562

BT - Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings

A2 - Braccini, Carlo

A2 - DeFloriani, Leila

A2 - Vernazza, Gianni

PB - Springer Verlag

ER -

Zidouri ABC, Chinveeraphan S, Sato M. Structural features by MCR expression for printed Arabic character recognition. In Braccini C, DeFloriani L, Vernazza G, editors, Image Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings. Springer Verlag. 1995. p. 557-562. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-60298-4_314

Structural features by MCR expression for printed Arabic character recognition

Abstract

Publication series

Bibliographical note

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this