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Off-line arabic handwritten word segmentation using rotational invariant segments features
S. Abdulla, , R.A. Salam
Published in
Volume: 5
Issue: 2
Pages: 200 - 208
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.
About the journal
JournalInternational Arab Journal of Information Technology
Open AccessNo
Concepts (4)
  •  related image
    Arabic character segmentation
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    Arabic words database
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    Cursive writing
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    Feature extraction