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AuthorKhan F.
AuthorBouridane A.
AuthorKhelifi F.
AuthorAlmotaeryi R.
AuthorAl-Maadeed, Somaya
Available date2022-05-19T10:23:13Z
Publication Date2014
Publication NameProceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/CoDIT.2014.6996979
URIhttp://hdl.handle.net/10576/31148
AbstractSegmentation 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.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectInformation retrieval systems
Text processing
Classification methods
Confidence interval
Global binarization
Multiple threshold
Projection profile
Sub words
Thresholding
Character recognition
TitleEfficient segmentation of sub-words within handwritten arabic words
TypeConference Paper
Pagination684-689
dc.accessType Abstract Only


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