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Specific Handwritten Chinese Character Recognition Based on Artificial Intelligence
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management.
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

As internet techniques are developing more and more quickly, internet becomes the

main way to communicate with the outside world. In this case, written information

on paper needs to be converted to digital information urgently, increasing the need

for handwritten character recognition. The aim of this work is to discuss methods

that can be used to recognize handwritten Chinese characters. We study geometric

features and clustering of handwritten Chinese characters from three aspects, which

are handwritten character preprocessing, feature extraction and clustering. To test

the correctness of our method, an application was built that could learn to recognize

five medium-hard handwritten Chinese characters by using a neural network.

Place, publisher, year, edition, pages
2013. , 31 p.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:hig:diva-14599OAI: oai:DiVA.org:hig-14599DiVA: diva2:630219
Subject / course
Computer science
Educational program
Computer science
Supervisors
Examiners
Available from: 2013-06-24 Created: 2013-06-18 Last updated: 2013-06-24Bibliographically approved

Open Access in DiVA

fulltext(878 kB)231 downloads
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fbf70cdbbf81054ebfc6a32fada3b306e6e245e328f13a8d9beff001baab100e7eb73771fc664d304aa054d772a59be38a49565a35c349858a9e4b068e57c605
Type fulltextMimetype application/pdf

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Xu, ZhengyanZhou, Yibing
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf