Text line extraction for historical document images

Saabni, Raid; Asi, Abedelkadir; El-Sana, Jihad

doi:10.1016/j.patrec.2013.07.007

Cited by 77 publications

(53 citation statements)

References 31 publications

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“…Saabni et al [26] computed an energy map based on the sign distance transform. Since the result map had negative values in the textlines and positive values in the background, minimal energy paths that pass between the textlines were extracted by using the dynamic programming.…”

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Textline detection in degraded historical document images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This paper presents a textline detection method for degraded historical documents.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 In order to address the challenges in historical documents such as document degradation, structure noise, and skews, we develop new methods for the binarization and textline extraction.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Textline detection in degraded historical document images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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“…Our algorithm differs from the above approach in the sense that we apply seam carving to directly compute the separating seams and not the medial ones. This results in a clearer separation of text lines with no cuts through letter components, which is a common phenomenon with the greedy approach of [4]. Furthermore, the use of seam carving for medial seam computation as in [4] can result in seams that jump over neighboring lines, especially in cases where the gaps between words are large compared to the distance between two consecutive text lines.…”

Section: Related Workmentioning

confidence: 96%

“…Our method is closely related to the fourth method proposed in [4], where the authors use a two-stage procedure to extract text lines from a grayscale image. First, seam carving is used to generate the medial seams of the manuscript page.…”

Section: Related Workmentioning

confidence: 99%

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Seam Carving for Text Line Extraction on Color and Grayscale Historical Manuscripts

Arvanitopoulos

Süsstrunk

2014

2014 14th International Conference on Frontiers in Handwriting Recognition

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Abstract-We propose a novel algorithm for automatic text line extraction on color and grayscale manuscript pages without prior binarization. Our algorithm is based on seam carving to compute separating seams between text lines. Seam carving is likely to produce seams that move through gaps between neighboring lines, if no information about the text geometry is incorporated into the problem. By constraining the optimization procedure inside the region between two consecutive text lines, we can produce robust separating seams that do not cut through word and line components. Extensive experimental evaluations on diverse manuscript pages show that we improve upon the state-of-the-art for grayscale text line extraction.

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“…The algorithm in [7] computes the distance transform directly from the gray scale images and generates two types of seams: the medial seams determine the text lines and the separating seams define the upper and lower boundaries of the text lines. Similarly, the work in [8] splits the document into vertical slices and applies a matching method on the result of projection profile in order to estimate the medial seam, then a modified version of seam carving procedure is used to compute the separating seam.…”

Section: Introductionmentioning

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 extraction for historical document images

Cited by 77 publications

References 31 publications

Textline detection in degraded historical document images

Textline detection in degraded historical document images

Seam Carving for Text Line Extraction on Color and Grayscale Historical Manuscripts

Segmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform

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