2012 10th IAPR International Workshop on Document Analysis Systems 2012
DOI: 10.1109/das.2012.20
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Arabic Handwritten Text Line Extraction by Applying an Adaptive Mask to Morphological Dilation

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Cited by 26 publications
(10 citation statements)
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“…A morphological dilation using a dynamic adaptive mask was applied to the documents for line extraction. The authors [25] achieved a precision rate of 96.3% and a recall rate of 96.7% on this database. In addition, Khayyat et al [26] proposed a partial segmentation algorithm to segment text lines into sub-words.…”
Section: B Experiments On Handwritten Documentsmentioning
confidence: 91%
“…A morphological dilation using a dynamic adaptive mask was applied to the documents for line extraction. The authors [25] achieved a precision rate of 96.3% and a recall rate of 96.7% on this database. In addition, Khayyat et al [26] proposed a partial segmentation algorithm to segment text lines into sub-words.…”
Section: B Experiments On Handwritten Documentsmentioning
confidence: 91%
“…The input of our system is a binarized text line. A method that was proposed by M. Al-Khayat et al [16] for text line segmentation was used. First, the Connected Components (CCs) of a text line were extracted.…”
Section: Our Methodologymentioning
confidence: 99%
“…In [20], a smearing method based on adaptive morphological dilation is proposed for Arabic handwritten text lines extraction. The horizontal PP is used to estimate the skew line.…”
Section: Related Workmentioning
confidence: 99%