Robust Chinese character recognition by selection of binary-based and grayscale-based classifier

Yoshinobu Hotta; Jun Sun; Yutaka Katsuyama; Satoshi Naoi

doi:10.1007/11669487_49

Robust Chinese character recognition by selection of binary-based and grayscale-based classifier

Yoshinobu Hotta^*, Jun Sun, Yutaka Katsuyama, Satoshi Naoi

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

As the spread of digital videos, digital cameras, and camera phones, lots of researches are reported about degraded character recognition. It is found that while the grayscale-based classifier is powerful for degraded character, the performance for clear character is not so good as binary-based classifier. In this paper, a dynamic classifier selection method is proposed to combine the two classifiers based on an estimation of the degradation level and the recognition reliability of the input character images. Experimental results show that the proposed method can achieve better recognition performance than the two individual ones.

Original language	English
Title of host publication	Document Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings
Pages	553-563
Number of pages	11
DOIs	https://doi.org/10.1007/11669487_49
Publication status	Published - 2006
Externally published	Yes
Event	7th International Workshop on Document Analysis Systems, DAS 2006 - Nelson, New Zealand Duration: 2006 Feb 13 → 2006 Feb 15

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3872 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Workshop on Document Analysis Systems, DAS 2006
Country/Territory	New Zealand
City	Nelson
Period	06/2/13 → 06/2/15

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/11669487_49

Cite this

Hotta, Y., Sun, J., Katsuyama, Y., & Naoi, S. (2006). Robust Chinese character recognition by selection of binary-based and grayscale-based classifier. In Document Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings (pp. 553-563). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3872 LNCS). https://doi.org/10.1007/11669487_49

Robust Chinese character recognition by selection of binary-based and grayscale-based classifier. / Hotta, Yoshinobu; Sun, Jun; Katsuyama, Yutaka et al.
Document Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings. 2006. p. 553-563 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3872 LNCS).

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

Hotta, Y, Sun, J, Katsuyama, Y & Naoi, S 2006, Robust Chinese character recognition by selection of binary-based and grayscale-based classifier. in Document Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3872 LNCS, pp. 553-563, 7th International Workshop on Document Analysis Systems, DAS 2006, Nelson, New Zealand, 06/2/13. https://doi.org/10.1007/11669487_49

Hotta Y, Sun J, Katsuyama Y, Naoi S. Robust Chinese character recognition by selection of binary-based and grayscale-based classifier. In Document Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings. 2006. p. 553-563. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11669487_49

Hotta, Yoshinobu ; Sun, Jun ; Katsuyama, Yutaka et al. / Robust Chinese character recognition by selection of binary-based and grayscale-based classifier. Document Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings. 2006. pp. 553-563 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "As the spread of digital videos, digital cameras, and camera phones, lots of researches are reported about degraded character recognition. It is found that while the grayscale-based classifier is powerful for degraded character, the performance for clear character is not so good as binary-based classifier. In this paper, a dynamic classifier selection method is proposed to combine the two classifiers based on an estimation of the degradation level and the recognition reliability of the input character images. Experimental results show that the proposed method can achieve better recognition performance than the two individual ones.",

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AB - As the spread of digital videos, digital cameras, and camera phones, lots of researches are reported about degraded character recognition. It is found that while the grayscale-based classifier is powerful for degraded character, the performance for clear character is not so good as binary-based classifier. In this paper, a dynamic classifier selection method is proposed to combine the two classifiers based on an estimation of the degradation level and the recognition reliability of the input character images. Experimental results show that the proposed method can achieve better recognition performance than the two individual ones.

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Robust Chinese character recognition by selection of binary-based and grayscale-based classifier

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