Handwritten Arabic Documents Segmentation into Text Lines using Seam Carving

Authors

DOI:

https://doi.org/10.9781/ijimai.2018.06.002

Keywords:

Arabic Documents, Handwritten Character Recognition, Text Line Segmentation, Projection Profile, Seam Carving
Supporting Agencies
We thank the Wellcome Library for providing a wide collection of old manuscript and digitized documents for free under creative commons license “Attribution 4.0 International (CC BY 4.0)” which grant researchers and enthusiasts the access to rare and interesting historical content, and we hope that other libraries take this as a model for sharing the knowledge and cultural heritage to the research community.

Abstract

Inspired from human perception and common text documents characteristics based on readability constraints, an Arabic text line segmentation approach is proposed using seam carving. Taking the gray scale of the image as input data, this technique offers better results at extracting handwritten text lines without the need for the binary representation of the document image. In addition to its fast processing time, its versatility permits to process a multitude of document types, especially documents presenting low text-to-background contrast such as degraded historical manuscripts or complex writing styles like cursive handwriting. Even if our focus in this paper was on Arabic text segmentation, this method is language independent. Tests on a public database of 123 handwritten Arabic documents showed a line detection rate of 97.5% for a matching score of 90%.

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References

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Published

2019-06-01
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How to Cite

Souhar, A. and Daldali, M. (2019). Handwritten Arabic Documents Segmentation into Text Lines using Seam Carving. International Journal of Interactive Multimedia and Artificial Intelligence, 5(5), 89–96. https://doi.org/10.9781/ijimai.2018.06.002

Issue

Vol. 5 No. 5 (2019): IJIMAI 2019 - Regular Issue.

Section

Regular Articles