Off-Line Arabic Handwritten Words Segmentation using Morphological Operators

• URL: http://arxiv.org/abs/2101.02797v1
• Date: Thu, 7 Jan 2021 23:38:53 GMT
• Title: Off-Line Arabic Handwritten Words Segmentation using Morphological Operators
• Authors: Nisreen AbdAllah and Serestina Viriri
• Abstract summary: The framework is proposed based on three steps: pre-processing, segmentation, and evaluation. The proposed model achieved the highest accuracy when compared with the related works.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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