Arabic Handwritten Text Line Extraction by Applying an Adaptive Mask to Morphological Dilation

Khayyat, Muna; Lam, Louisa; Suen, Ching Y.; Yin, Fei; Liu, Cheng‐Lin

doi:10.1109/das.2012.20

Cited by 27 publications

(10 citation statements)

References 7 publications

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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%

Novel Handwritten Words and Documents Databases of Five Middle Eastern Languages

Nobile

Khayyat

Lam

et al. 2014

2014 14th International Conference on Frontiers in Handwriting Recognition

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This paper introduces new handwritten databases of selected words in the five Middle-Eastern languages of Arabic, Dari, Farsi, Pashto and Urdu. The databases share a common lexicon of forty words that are related to finance and are used in daily life. The five databases have been collected from over 1600 native writers located in four countries. Recognition results for each of the databases are also presented. Results come from three classifiers (Support Vector Machines, Modified Quadratic Discriminant Function. and Multi-layer Perceptron) which were implemented for recognition of the words based on gradient features. Given the diversity of the data, the results demonstrate the effectiveness of the implemented process in learning and recognizing samples of handwritten words from different languages.In addition, full page handwritten documents of each language are presented, with approximately forty pages per language. Each document has associated groundtruth information.

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Section: B Experiments On Handwritten Documentsmentioning

confidence: 91%

Novel Handwritten Words and Documents Databases of Five Middle Eastern Languages

Nobile

Khayyat

Lam

et al. 2014

2014 14th International Conference on Frontiers in Handwriting Recognition

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“…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%

End-Shape Recognition for Arabic Handwritten Text Segmentation

Jamal

Nobile

Suen

2014

Advanced Information Systems Engineering

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Text segmentation is an essential pre-processing stage for many systems such as text recognition and word spotting. However, few methods have been published for Arabic text segmentation. In Arabic handwritten documents, separating text into words is challenging due to the enormous different Arabic handwriting styles. In this paper, we present a new segmentation methodology of an Arabic handwritten text line into words. Our proposed approach of text segmentation utilizes the knowledge of Arabic writing characteristics. This method shows promising results.

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“…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%

Arabic handwritten text line extraction using connected component analysis from a multi agent perspective

Boulid

Souhar

Elkettani

2015

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)

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This paper presents an approach to extract curved text lines from Arabic handwritten documents, based on the perception mechanisms involved in the human reading process. Our approach is based on multi-agent systems to detect and group connected components that belong to the same line. This proposed system makes use of information about features and arrangement of those components. Experimental results on a data-set of Arabic handwritten documents show that this approach is a promising solution for extracting handwritten curved text lines.

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Arabic Handwritten Text Line Extraction by Applying an Adaptive Mask to Morphological Dilation

Cited by 27 publications

References 7 publications

Novel Handwritten Words and Documents Databases of Five Middle Eastern Languages

Novel Handwritten Words and Documents Databases of Five Middle Eastern Languages

End-Shape Recognition for Arabic Handwritten Text Segmentation

Arabic handwritten text line extraction using connected component analysis from a multi agent perspective

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