An improved skew angle detection and correction technique for historical scanned documents using morphological skeleton and progressive probabilistic hough transform

Boudraa, Omar; Hidouci, Walid Khaled; Michelucci, Dominique

doi:10.1109/icee-b.2017.8192043

Cited by 11 publications

(5 citation statements)

References 20 publications

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“…Based on corner features, Ahmed gari et al [ 26 ] proposed a method by applying Hough transform to Harris interest points. In order to eliminate the interference caused by noises, Omar boudraa et al [ 27 ] introduces a method based on morphological skeleton to eliminate redundant pixels and noise and retains the central curve of image components simultaneously. Geometric constraints are also applied to skew correction.…”

Section: Related Workmentioning

confidence: 99%

A Novel Adaptive Deskewing Algorithm for Document Images

Bao

Yang

et al. 2022

Sensors

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Document scanning often suffers from skewing, which may seriously influence the efficiency of Optical Character Recognition (OCR). Therefore, it is necessary to correct the skewed document before document image information analysis. In this article, we propose a novel adaptive deskewing algorithm for document images, which mainly includes Skeleton Line Detection (SKLD), Piecewise Projection Profile (PPP), Morphological Clustering (MC), and the image classification method. The image type is determined firstly based on the image’s layout feature. Thus, adaptive correcting is applied to deskew the image according to its type. Our method maintains high accuracy on the Document Image Skew Estimation Contest (DISEC’2013) and PubLayNet datasets, which achieved 97.6% and 80.1% accuracy, respectively. Meanwhile, extensive experiments show the superiority of the proposed algorithm.

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Section: Related Workmentioning

confidence: 99%

A Novel Adaptive Deskewing Algorithm for Document Images

Bao

Yang

et al. 2022

Sensors

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“…Hough transform [15][16][17][18] High accuracy High computation cost, large memory, and limitation in handing curved text-lines Nearest neighbor [20,21] Robust, fast, and not limited to range of skew angle Design for special script, very sensitive to noise…”

Section: Category Advantages Disadvantagesmentioning

confidence: 99%

“…They minimized the amount of computation needed to detect lines by exploiting the difference in the fraction of votes needed to reliably detect lines with different numbers of supporting points. Boudraa [18] introduced morphological skeleton method to remove the redundant pixels and only retain the central curves of the input document image, which achieved high accuracy but reduced the speed of angle detection.Nearest neighbor (NN) method is based on finding the connected components of a document. Hashizume et al [19] first proposed NN method.…”

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confidence: 99%

An Efficient Document Skew Detection Method Using Probability Model and Q Test

Huang

Chen

et al. 2019

Electronics

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Document skew detection is one of the key technologies in most of the document analysis systems. However, existing skew detection methods either have low accuracy or require a large amount of computation. To achieve a good tradeoff between efficiency and performance, we propose a novel skew detection approach based on bounding boxes, probability model, and Dixon’s Q test. Firstly, bounding boxes are used to pick out the eligible connected components (ECC). Then, we calculate the slopes of the skew document with the probability model. Finally, we find the optimal result with Dixon’s Q test and projection profile method. Moreover, the proposed method can detect the skew angle in a wider range. The experimental results show that our skew detection algorithm can achieve high speed and accuracy simultaneously compared with existing algorithms.

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“…However, this method cannot give a satisfactory result when the input image had a shadow region or shadow background and lighting effects. But in [5] an effective binarization technique (Nick method) is proposed using the following formula  …”

Section: Binarizationmentioning

confidence: 99%

“…To get superior and high accuracy OCR outputs, images being passed to the OCR system have to be checked and corrected from any skews [2]. To overcome these, several methods for skew angle detection and free skew technique to improve the accuracy of OCR systems have been proposed, but these [3][4][5][6][7][8][9] do not discuss about it.…”

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confidence: 99%

Image Purification Technique for Myanmar OCR Applying Skew Angle Detection and Free Skew

Lwin

2019

IJSRST

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Optical Character Recognition (OCR) is a technology widely adopted for automatic translation of hardcopy text to editable text. The language dependence of the technology makes it far less developed for less popular languages like Myanmar language. Also, the uniqueness and complexity of the Myanmar text system such as touching and complex characters have continued to pose serious challenges to several OCR investigators. In this paper, we propose a new technique to development Myanmar OCR system. Our technique implement skew angle detection and free skew, noisy border correction, extra page elimination, line segmentation from scanned images of Myanmar text. Performance of the proposed method is tested with 430 documents comprising different printed and handwritten Myanmar text of various fonts, sizes, multi-column, tables, stamps or photos, background effects. Our method give an accuracy of 100% for line segmentation and 99.92% for skew angle detection and free skew. The ability of our method to effectively implement global and local skew angle detection, free skew and line segmentation in different handwritten and digital text images of the Myanmar character set with high accuracies confirms the robustness of the technique, its reliability and its suitability for application in many other related languages.

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An improved skew angle detection and correction technique for historical scanned documents using morphological skeleton and progressive probabilistic hough transform

Cited by 11 publications

References 20 publications

A Novel Adaptive Deskewing Algorithm for Document Images

A Novel Adaptive Deskewing Algorithm for Document Images

An Efficient Document Skew Detection Method Using Probability Model and Q Test

Image Purification Technique for Myanmar OCR Applying Skew Angle Detection and Free Skew

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