Arabic hand-written text-line extraction

Zahour, Abderrazak; Taconet, Bruno; Mercy, Pascal; Ramdane, Saïd

doi:10.1109/icdar.2001.953799

Cited by 86 publications

(57 citation statements)

References 4 publications

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“…These methods were able to alleviate the skew problem; however, they have limitations in handling the curved textlines. Zahour et al [32] proposed a partial projection procedure: they partitioned an input page into columns and drew horizontal strokes in each column. The horizontal strokes were connected to construct separating lines between the adjacent textlines.…”

Section: Methods On Textline Detection In Handwritten Documentsmentioning

confidence: 99%

Textline detection in degraded historical document images

Ahn

Ryu

Koo

et al. 2017

J Image Video Proc.

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This paper presents a textline detection method for degraded historical documents. Our method follows a conventional two-step procedure that the binarization is first performed and then the textlines are extracted from the binary image. In order to address the challenges in historical documents such as document degradation, structure noise, and skews, we develop new methods for the binarization and textline extraction. First, we improve the performance of binarization by detecting the non-text regions and processing only text regions. We also improve the textline detection method by extracting main textblock and compensating the skew angle and writing style. Experimental results show that the proposed method yields the state-of-the-art performance for several datasets.

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Section: Methods On Textline Detection In Handwritten Documentsmentioning

confidence: 99%

Textline detection in degraded historical document images

Ahn

Ryu

Koo

et al. 2017

J Image Video Proc.

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show abstract

“…Method for overlapping and touching components detects such components during the grouping process. At present, the conflict occurs between the two alignments [17]. Further, it applies a set of rules to label overlapping or touching components.…”

Section: Introductionmentioning

confidence: 99%

Text Line Segmentation With Water Flow Algorithm Based on Power Function

Brodić

2015

Journal of Electrical Engineering

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This manuscript proposes an extension to the water flow algorithm for text line segmentation. Basic algorithm assumes hypothetical water flows under few specified angles of the document image frame from left to right and vice versa. As a result, unwetted image regions that incorporate text are extracted. These regions are of the major importance for text line segmentation. The extension of the basic algorithm means modification of water flow function that creates the unwetted region. Hence, the linear water flow function used in the basic algorithm is changed with its power function counterpart. Extended method was tested, examined and evaluated under different text samples. Results are encouraging due to improving text line segmentation which is a key process stage.

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“…The performance of connected component based methods on a handwritten document can also be improved by estimating the local orientation of the text line and using it to guide the merging of connected components [2]. Other researchers proposed different assumptions for their specific case [16] or for a specific script [17].…”

Section: Text Line Segmentationmentioning

confidence: 99%

Script-Independent Text Line Segmentation in Freestyle Handwritten Documents

Li¹,

Zheng²,

Doermann³

et al. 2006

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Text line segmentation in freestyle handwritten documents remains an open document analysis problem. Curvilinear text lines and small gaps between neighboring text lines present a challenge to algorithms developed for machine printed or hand-printed documents. In this paper, we propose a novel approach based on density estimation and a state-of-the-art image segmentation technique, the level set method. From an input document image, we estimate a probability map, where each element represents the probability that the underlying pixel belongs to a text line. The level set method is then exploited to determine the boundary of neighboring text lines by evolving an initial estimate. Unlike most connected component based methods [1,2], the proposed algorithm does not use any script-specific knowledge. Extensive quantitative experiments on freestyle handwritten documents with diverse scripts, such as Arabic, Chinese, Korean, and Hindi, demonstrate that our algorithm consistently outperforms previous methods [3,1,2]. Further experiments show the proposed algorithm is robust to scale change, rotation, and noise. Keywords: Handwritten Text Line Segmentation, Document Image Analysis, Density Estimation, Level Set MethodsThe support of this research by the Department of Defense under contract MDA-9040-2C-0406 is gratefully acknowledged. 1 Report Documentation PageForm Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.

show abstract

Arabic hand-written text-line extraction

Cited by 86 publications

References 4 publications

Textline detection in degraded historical document images

Textline detection in degraded historical document images

Text Line Segmentation With Water Flow Algorithm Based on Power Function

Script-Independent Text Line Segmentation in Freestyle Handwritten Documents

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