Artificial neural network based sinhala character recognition

H. Waruna H Premachandra; Chinthaka Premachandra; Tomotaka Kimura; Hiroharu Kawanaka

doi:10.1007/978-3-319-46418-3_53

Artificial neural network based sinhala character recognition

H. Waruna H Premachandra, Chinthaka Premachandra, Tomotaka Kimura, Hiroharu Kawanaka

Department of Electronic Engineering

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

1 Citation (Scopus)

Abstract

Sinhala is the main language spoken by the majority of the population of Sri Lanka. There is a clear need for an optical character recognition (OCR) system for the Sinhala language. However, the language contains very similar characters, which makes it very difficult to distinguish them except on feature analysis. The character recognition rates of previous systems proposed for Sinhala character recognition are low, and so further improvement is needed. Consequently, in this paper, we propose a new Sinhala character recognition method that uses character geometry features and artificial neural network (ANN). The results of experiments conducted using various documentary images of the Sinhala language indicate that the proposed method has better character recognition performance than conventional methods.

Original language	English
Title of host publication	Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings
Publisher	Springer Verlag
Pages	594-603
Number of pages	10
Volume	9972 LNCS
ISBN (Print)	9783319464176
DOIs	https://doi.org/10.1007/978-3-319-46418-3_53
Publication status	Published - 2016
Event	International Conference on Computer Vision and Graphics, ICCVG 2016 - Warsaw, Poland Duration: 2016 Sep 19 → 2016 Sep 21

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9972 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	International Conference on Computer Vision and Graphics, ICCVG 2016
Country/Territory	Poland
City	Warsaw
Period	16/9/19 → 16/9/21

Keywords

Artificial neural networks
Character geometry features
Character recognition
Sinhala script

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-46418-3_53

Cite this

Premachandra, H. W. H., Premachandra, C., Kimura, T., & Kawanaka, H. (2016). Artificial neural network based sinhala character recognition. In Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings (Vol. 9972 LNCS, pp. 594-603). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9972 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46418-3_53

Artificial neural network based sinhala character recognition. / Premachandra, H. Waruna H; Premachandra, Chinthaka; Kimura, Tomotaka et al.

Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings. Vol. 9972 LNCS Springer Verlag, 2016. p. 594-603 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9972 LNCS).

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

Premachandra, HWH, Premachandra, C, Kimura, T & Kawanaka, H 2016, Artificial neural network based sinhala character recognition. in Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings. vol. 9972 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9972 LNCS, Springer Verlag, pp. 594-603, International Conference on Computer Vision and Graphics, ICCVG 2016, Warsaw, Poland, 16/9/19. https://doi.org/10.1007/978-3-319-46418-3_53

Premachandra HWH, Premachandra C, Kimura T, Kawanaka H. Artificial neural network based sinhala character recognition. In Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings. Vol. 9972 LNCS. Springer Verlag. 2016. p. 594-603. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46418-3_53

Premachandra, H. Waruna H ; Premachandra, Chinthaka ; Kimura, Tomotaka et al. / Artificial neural network based sinhala character recognition. Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings. Vol. 9972 LNCS Springer Verlag, 2016. pp. 594-603 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Sinhala is the main language spoken by the majority of the population of Sri Lanka. There is a clear need for an optical character recognition (OCR) system for the Sinhala language. However, the language contains very similar characters, which makes it very difficult to distinguish them except on feature analysis. The character recognition rates of previous systems proposed for Sinhala character recognition are low, and so further improvement is needed. Consequently, in this paper, we propose a new Sinhala character recognition method that uses character geometry features and artificial neural network (ANN). The results of experiments conducted using various documentary images of the Sinhala language indicate that the proposed method has better character recognition performance than conventional methods.",

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AB - Sinhala is the main language spoken by the majority of the population of Sri Lanka. There is a clear need for an optical character recognition (OCR) system for the Sinhala language. However, the language contains very similar characters, which makes it very difficult to distinguish them except on feature analysis. The character recognition rates of previous systems proposed for Sinhala character recognition are low, and so further improvement is needed. Consequently, in this paper, we propose a new Sinhala character recognition method that uses character geometry features and artificial neural network (ANN). The results of experiments conducted using various documentary images of the Sinhala language indicate that the proposed method has better character recognition performance than conventional methods.

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Artificial neural network based sinhala character recognition

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Keywords

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