Adaptive SEJONG-NET for on-line Hangul recognition

Hyeyoung Park, Kwanyong Lee, Hyeran Byun, Yillbyung Lee

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationPRICAI 1996
Subtitle of host publicationTopics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings
EditorsNorman Foo, Randy Goebel
PublisherSpringer Verlag
Pages447-458
Number of pages12
ISBN (Print)3540615326, 9783540615323
DOIs
Publication statusPublished - 1996 Jan 1
Event4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996 - Cairns, Australia
Duration: 1996 Aug 261996 Aug 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1114
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996
CountryAustralia
CityCairns
Period96/8/2696/8/30

Fingerprint

Conceptual Graphs
Vertex of a graph
Adaptability
Computer simulation
Curvature
Stroke
Computer Simulation
Graph in graph theory
Model
Concepts

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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 ; Lee, Yillbyung. / 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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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; Lee, Yillbyung.

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 proceedingConference contribution

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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 - 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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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)). https://doi.org/10.1007/3-540-61532-6_38