Adaptive SEJONG-NET for on-line Hangul recognition

Hyeyoung Park; Kwanyong Lee; Hyeran Byun; Yillbyung Lee

doi:10.1007/3-540-61532-6_38

Adaptive SEJONG-NET for on-line Hangul recognition

Hyeyoung Park, Kwanyong Lee, Hyeran Byun, Yillbyung Lee

College of Computing

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

1 Citation (Scopus)

Abstract

In this paper, a revised SEJONG-NET with adaptability for recognizing transformed on-line Hangul pattern is proposed. It is based on the structural characteristics of Hangul and the hypotheses on the processes of human Hangul recognition. Unlike the existing SEJONG-NET, the proposed model extracts the information about the orientation and the curvature of strokes in the lower layers. In the higher layers, it represents the information on graphemes as conceptual graphs, and detects a particular grapheme using the conceptual graph. The conceptual graph is composed of two kinds of nodes, concept nodes and relation nodes. The concept node has the orientation and curvature information, and the relation node describes the positional relations between two concept nodes. Through the computer simulations, we showed that the adaptive SEJONG-NET could recognize the transformed Hangul patterns after training the basic grapheme patterns, and also that untrained or severely deformed patterns can be efficiently recognized by creating a new graph or adjusting the values of the existing conceptual graphs. Hence, SEJONG-NET with adaptability can be considered as an efficient model for recognizing Hangul patterns with transformation.

Original language	English
Title of host publication	PRICAI 1996
Subtitle of host publication	Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Editors	Norman Foo, Randy Goebel
Publisher	Springer Verlag
Pages	447-458
Number of pages	12
ISBN (Print)	3540615326, 9783540615323
DOIs	https://doi.org/10.1007/3-540-61532-6_38
Publication status	Published - 1996
Event	4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996 - Cairns, Australia Duration: 1996 Aug 26 → 1996 Aug 30

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1114
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996
Country/Territory	Australia
City	Cairns
Period	96/8/26 → 96/8/30

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1996.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-61532-6_38

Cite this

Park, H., Lee, K., Byun, H., & Lee, Y. (1996). Adaptive SEJONG-NET for on-line Hangul recognition. In N. Foo, & R. Goebel (Eds.), PRICAI 1996: Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings (pp. 447-458). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1114). Springer Verlag. https://doi.org/10.1007/3-540-61532-6_38

Park, Hyeyoung ; Lee, Kwanyong ; Byun, Hyeran et al. / Adaptive SEJONG-NET for on-line Hangul recognition. PRICAI 1996: Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings. editor / Norman Foo ; Randy Goebel. Springer Verlag, 1996. pp. 447-458 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Adaptive SEJONG-NET for on-line Hangul recognition",

abstract = "In this paper, a revised SEJONG-NET with adaptability for recognizing transformed on-line Hangul pattern is proposed. It is based on the structural characteristics of Hangul and the hypotheses on the processes of human Hangul recognition. Unlike the existing SEJONG-NET, the proposed model extracts the information about the orientation and the curvature of strokes in the lower layers. In the higher layers, it represents the information on graphemes as conceptual graphs, and detects a particular grapheme using the conceptual graph. The conceptual graph is composed of two kinds of nodes, concept nodes and relation nodes. The concept node has the orientation and curvature information, and the relation node describes the positional relations between two concept nodes. Through the computer simulations, we showed that the adaptive SEJONG-NET could recognize the transformed Hangul patterns after training the basic grapheme patterns, and also that untrained or severely deformed patterns can be efficiently recognized by creating a new graph or adjusting the values of the existing conceptual graphs. Hence, SEJONG-NET with adaptability can be considered as an efficient model for recognizing Hangul patterns with transformation.",

author = "Hyeyoung Park and Kwanyong Lee and Hyeran Byun and Yillbyung Lee",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1996.; 4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996 ; Conference date: 26-08-1996 Through 30-08-1996",

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Park, H, Lee, K, Byun, H & Lee, Y 1996, Adaptive SEJONG-NET for on-line Hangul recognition. in N Foo & R Goebel (eds), PRICAI 1996: Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1114, Springer Verlag, pp. 447-458, 4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996, Cairns, Australia, 96/8/26. https://doi.org/10.1007/3-540-61532-6_38

Adaptive SEJONG-NET for on-line Hangul recognition. / Park, Hyeyoung; Lee, Kwanyong; Byun, Hyeran et al.
PRICAI 1996: Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings. ed. / Norman Foo; Randy Goebel. Springer Verlag, 1996. p. 447-458 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1114).

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

TY - GEN

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AU - Park, Hyeyoung

AU - Lee, Kwanyong

AU - Byun, Hyeran

AU - Lee, Yillbyung

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 1996.

PY - 1996

Y1 - 1996

N2 - In this paper, a revised SEJONG-NET with adaptability for recognizing transformed on-line Hangul pattern is proposed. It is based on the structural characteristics of Hangul and the hypotheses on the processes of human Hangul recognition. Unlike the existing SEJONG-NET, the proposed model extracts the information about the orientation and the curvature of strokes in the lower layers. In the higher layers, it represents the information on graphemes as conceptual graphs, and detects a particular grapheme using the conceptual graph. The conceptual graph is composed of two kinds of nodes, concept nodes and relation nodes. The concept node has the orientation and curvature information, and the relation node describes the positional relations between two concept nodes. Through the computer simulations, we showed that the adaptive SEJONG-NET could recognize the transformed Hangul patterns after training the basic grapheme patterns, and also that untrained or severely deformed patterns can be efficiently recognized by creating a new graph or adjusting the values of the existing conceptual graphs. Hence, SEJONG-NET with adaptability can be considered as an efficient model for recognizing Hangul patterns with transformation.

AB - In this paper, a revised SEJONG-NET with adaptability for recognizing transformed on-line Hangul pattern is proposed. It is based on the structural characteristics of Hangul and the hypotheses on the processes of human Hangul recognition. Unlike the existing SEJONG-NET, the proposed model extracts the information about the orientation and the curvature of strokes in the lower layers. In the higher layers, it represents the information on graphemes as conceptual graphs, and detects a particular grapheme using the conceptual graph. The conceptual graph is composed of two kinds of nodes, concept nodes and relation nodes. The concept node has the orientation and curvature information, and the relation node describes the positional relations between two concept nodes. Through the computer simulations, we showed that the adaptive SEJONG-NET could recognize the transformed Hangul patterns after training the basic grapheme patterns, and also that untrained or severely deformed patterns can be efficiently recognized by creating a new graph or adjusting the values of the existing conceptual graphs. Hence, SEJONG-NET with adaptability can be considered as an efficient model for recognizing Hangul patterns with transformation.

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M3 - Conference contribution

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SN - 3540615326

SN - 9783540615323

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

SP - 447

EP - 458

BT - PRICAI 1996

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PB - Springer Verlag

T2 - 4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996

Y2 - 26 August 1996 through 30 August 1996

ER -

Park H, Lee K, Byun H, Lee Y. Adaptive SEJONG-NET for on-line Hangul recognition. In Foo N, Goebel R, editors, PRICAI 1996: Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Springer Verlag. 1996. p. 447-458. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-61532-6_38

Adaptive SEJONG-NET for on-line Hangul recognition

Abstract

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