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arXiv · 2101.02797

Off-Line Arabic Handwritten Words Segmentation using Morphological Operators

Nisreen AbdAllah·Serestina Viriri
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Abstract

The main aim of this study is the assessment and discussion of a model for hand-written Arabic through segmentation. The framework is proposed based on three steps: pre-processing, segmentation, and evaluation. In the pre-processing step, morphological operators are applied for Connecting Gaps (CGs) in written words. Gaps happen when pen lifting-off during writing, scanning documents, or while converting images to binary type. In the segmentation step, first removed the small diacritics then bounded a connected component to segment offline words. Huge data was utilized in the proposed model for applying a variety of handwriting styles so that to be more compatible with real-life applications. Consequently, on the automatic evaluation stage, selected randomly 1,131 images from the IESK-ArDB database, and then segmented into sub-words. After small gaps been connected, the model performance evaluation had been reached 88% against the standard ground truth of the database. The proposed model achieved the highest accuracy when compared with the related works.

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BibTeXRIS

Nisreen AbdAllah, Serestina Viriri. 2021-01-07. Off-Line Arabic Handwritten Words Segmentation using Morphological Operators. https://doi.org/10.5121/sipij.2020.11602

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