A three-level classifier: Fuzzy C Means, Support Vector Machine and unique pixels for Arabic handwritten digits

Maen Takruri*, Rami Al-Hmouz, Ahmed Al-Hmouz

*Corresponding author for this work

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

6 Citations (Scopus)


In this study, we present a classification approach for handwritten Arabic digits (symbols). Like numbers in other languages, Arabic numbers consists of nine digits. Character images of Arabic digits are similar in the sense that one single classifier will not give a reliable classification rate. Therefore, the implementation of more levels of classification is important for the realization. We introduce Fuzzy C-Means based classifier for the lower level and Support Vector Machine SVM for the second level when more details are required and finally confirmation of classification will be through unique pixels. The unique pixel method forms the third classification level. It works on determining the pixel areas that are unique to each digit. The unique pixel method decision is compared with decision of the lower classifier (FCM) and top classifier (SVM). The algorithm is tested on 3510 images. The overall testing accuracy reported is 88%.

Original languageEnglish
Title of host publication2014 World Symposium on Computer Applications and Research, WSCAR 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479928057
Publication statusPublished - Oct 3 2014
Externally publishedYes
Event2014 World Symposium on Computer Applications and Research, WSCAR 2014 - Sousse, Tunisia
Duration: Jan 18 2014Jan 20 2014


Conference2014 World Symposium on Computer Applications and Research, WSCAR 2014


  • Arabic numbers
  • Fuzzy- C Mean
  • OCR
  • SVM

ASJC Scopus subject areas

  • Computer Science Applications

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