Off-line arabic handwritten word segmentation using rotational invariant segments features

Shubair Abdulla*, Amer Al-Nassiri, Rosalina Abdul Salam

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


This paper describes a new segmentation algorithm for handwritten Arabic characters using Rotational Invariant Segments Features (RISF). The algorithm evaluates a large set of curved segments or strokes through the image of the input Arabic word or subword using a dynamic feature extraction technique then nominates a small optimal subset of cuts for segmentation. All the directions of stroke are converted to two main segments: '+' and w'-' RISF. A list of nominated segmentation points are prepared from the '+' segments and evaluated according to special conditions to locate the final segmentation points. The RISF algorithm was tested by using our new designed database AHD/AUST and the IFN/ENIT database. It has achieved a high segmentation rate of 95.66% on AHD/AUST and 90.58% on IFN/ENIT handwritten Arabic databases.

Original languageEnglish
Pages (from-to)200-208
Number of pages9
JournalInternational Arab Journal of Information Technology
Issue number2
Publication statusPublished - Apr 2008
Externally publishedYes


  • Arabic character segmentation
  • Arabic words database
  • Cursive writing
  • Feature extraction

ASJC Scopus subject areas

  • Computer Science(all)

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