Text Line Segmentation of Historical Arabic Documents

Zahour, Abderrazak; Likforman-Sulem, Laurence; Boussalaa, W.; Taconet, Bruno

doi:10.1109/icdar.2007.4378691

Cited by 43 publications

(22 citation statements)

References 5 publications

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“…Also, the separation of vertically connected characters is not considered in these approaches. Similar problems arise to other methodologies as well [7,9,16].…”

Section: Introductionmentioning

confidence: 96%

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Text line detection in handwritten documents

Louloudis

Gatos

Pratikakis

et al. 2008

Pattern Recognition

110

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“…Also, the separation of vertically connected characters is not considered in these approaches. Similar problems arise to other methodologies as well [7,9,16].…”

Section: Introductionmentioning

confidence: 96%

“…Finally, in Ref. [16], a text line segmentation method for printed or handwritten historical Arabic is presented. Documents are first classified into two classes using a K-means scheme.…”

Section: Related Workmentioning

confidence: 99%

Text line detection in handwritten documents

Louloudis

Gatos

Pratikakis

et al. 2008

Pattern Recognition

110

View full text Add to dashboard Cite

“…The resulted zones that do not match any zone in the ground truth are counted as false positive (FP) and the zones in the data set that are left unmatched are considered false negative (FN). Therefore, we count precision, recall and F1-score as follows: (10) (11) (12) According to the tests we obtained a F1-Score respectively of 95.8 % and 90.5 % for the MS-threshold values of 90% and 95%. Table II compares the score of the proposed method with other methods tested on the same data set.…”

Section: Experimentationmentioning

confidence: 99%

Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes

Boulid¹,

Souhar²,

Elkettani³

2016

IJIMAI

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-In a character recognition systems, the segmentation phase is critical since the accuracy of the recognition depend strongly on it. In this paper we present an approach based on Markov Decision Processes to extract text lines from binary images of Arabic handwritten documents. The proposed approach detects the connected components belonging to the same line by making use of knowledge about features and arrangement of those components. The initial results show that the system is promising for extracting Arabic handwritten lines.

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“…12). In order to cope with the problem of curved lines, the idea is to divide the document into vertical slices and then analyzing each slice separately [20,8].…”

Section: Projection Profilementioning

confidence: 99%

Segmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform

Souhar¹,

Boulid²,

Ameur³

et al. 2017

IJIMAI

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A crucial task in character recognition systems is the segmentation of the document into text lines and especially if it is handwritten. When dealing with non-Latin document such as Arabic, the challenge becomes greater since in addition to the variability of writing, the presence of diacritical points and the high number of ascender and descender characters complicates more the process of the segmentation. To remedy with this complexity and even to make this difficulty an advantage since the focus is on the Arabic language which is semi-cursive in nature, a method based on the Watershed Transform technique is proposed. Tested on «Handwritten Arabic Proximity Datasets» [21] a segmentation rate of 93% for a 95% of matching score is achieved.

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Text Line Segmentation of Historical Arabic Documents

Cited by 43 publications

References 5 publications

Text line detection in handwritten documents

Text line detection in handwritten documents

Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes

Segmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform

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