Efficient segmentation of sub-words within handwritten arabic words

Khan, Faraz, Bouridane, Ahmed, Khelifi, Fouad, Almotaeryi, Resheed and Al-Maadeed, Somaya (2014) Efficient segmentation of sub-words within handwritten arabic words. In: Codit'14 - 2nd International Conference on Control, Decision and Information Technologies, 3rd - 5th November 2014, Metz, France.

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Official URL: http://dx.doi.org/10.1109/CoDIT.2014.6996979


Segmentation is considered as a core step for any recognition or classification method and for the text within any document to be effectively recognized it must be segmented accurately. In this paper a text and writer independent algorithm for the segmentation of sub-words in Arabic words has been presented. The concept is based around the global binarization of an image at various thresholding levels. When each sub-word or Part of Arabic Word (PAW) within the image being investigated is processed at multiple threshold levels a cluster graph is obtained where each cluster represents the individual sub-words of that word. Once the clusters are obtained the task of segmentation is managed by simply selecting the respective cluster automatically which is achieved using the 95% confidence interval on the processed data generated by the accumulated graph. The presented algorithm was tested on 537 randomly selected words from the AHTID/MW database and the results showed that 95.3% of the sub-words or PAW were correctly segmented and extracted. The proposed method has shown considerable improvement over the projection profile method which is commonly used to segment sub-words or PAW.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: handwritten character recognition; image segmentation; text analysis; word processing
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 06 Feb 2015 16:16
Last Modified: 12 Oct 2019 22:56
URI: http://nrl.northumbria.ac.uk/id/eprint/21341

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