Artificial neural network based sinhala character recognition

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


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 languageEnglish
Title of host publicationComputer Vision and Graphics - International Conference, ICCVG 2016, Proceedings
PublisherSpringer Verlag
Number of pages10
Volume9972 LNCS
ISBN (Print)9783319464176
Publication statusPublished - 2016
EventInternational Conference on Computer Vision and Graphics, ICCVG 2016 - Warsaw, Poland
Duration: 2016 Sept 192016 Sept 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9972 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


OtherInternational Conference on Computer Vision and Graphics, ICCVG 2016


  • Artificial neural networks
  • Character geometry features
  • Character recognition
  • Sinhala script

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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