Skew correction and line extraction in binarized printed text images

Li, Wei; Breier, Matthias; Merhof, Dorit

doi:10.1109/icip.2015.7350843

Cited by 4 publications

(5 citation statements)

References 18 publications

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“…Text lines in document images are often not aligned with the predictable direction, they are skewed. However, many text lines analysis processes and OCR engines require to skew corrected documents images and credible text line extraction for achieving perfect tesseract OCR performance [12].…”

Section: • Skew Correctionmentioning

confidence: 99%

“…Image Detection and Recognition is a classic machine learning and Deep learning problem. It is a challenging job to detect an object or to recognize a documents image from a digital image [12]. Tesseract OCR performs in two different steps: recognition and detection.…”

Section: B Image Detection and Recognitionmentioning

confidence: 99%

“…The detect can apply for line detect, word detect and character detect. Secondly, text recognition is performed to extract the text from document images and we can extract and recognize the text in images [12].…”

Section: B Image Detection and Recognitionmentioning

confidence: 99%

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Tesseract OCR Recognition Based on Arabic Machine-Printed Document

Ramteke,

Al Maamari

2023

Advances in Intelligent Systems Research

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This paper provides technical aspects and the context of Recognizing and Detecting Arabic characters using Tesseract OCR Engine. OCR engine is freely available and gives a better result and also is supporting many languages such as Arabic etc. The procedure begins by transforming the Arabic documents into machine format (scanning) and then recognizing as well as extracting the text using the PyTesseract library. The OCR is a system that can afford the considerable values of split errors, particularly while working with cursive languages like the Arabic language with repeated overlapping between letters. Moreover, The performance is 99.5 accuracy in OCR-tesseract for converting the Arabic image documents to text editable.

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Section: • Skew Correctionmentioning

confidence: 99%

Section: B Image Detection and Recognitionmentioning

confidence: 99%

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Tesseract OCR Recognition Based on Arabic Machine-Printed Document

Ramteke,

Al Maamari

2023

Advances in Intelligent Systems Research

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“…Mathematical Problems in Engineering [30][31][32][33]. ose skew detection and correction algorithms are mainly aiming at detecting the deviation of the document orientation angle from the horizontal or vertical direction.…”

Section: Skew Correction Algorithmmentioning

confidence: 99%

An Improved Tool Wear Monitoring Method Using Local Image and Fractal Dimension of Workpiece

Yu¹,

Wang

Zhang³

et al. 2021

Mathematical Problems in Engineering

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Tool wear is a key factor that dominates the surface quality and distinctly influences the generated workpiece surface texture. In order to realize accurate evaluation of the tool wear from the generated workpiece surface after machining process, a new tool wear monitoring method is developed by fractal dimension of the acquired workpiece surface digital image. A self-made simple apparatus is employed to capture the local digital images around the region of interest. In addition, a skew correction method based on local fast Fourier transformation energy is also proposed for the surface texture direction adjustment. Furthermore, the tool wear quantitative evaluation was derived based on fractal dimension utilizing its high reliability for inherent irregularity description. The proposed tool wear monitoring method has verified its feasibility as well as its effectiveness in actual milling experiments using the material of AISI 1045 in a vertical machining center. Testing results demonstrate that the proposed method was capable of tool wear condition evaluation.

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“…Hough transform, projection characteristics, Fourier transform and shearlet transform are algorithms commonly used for skew correction [14][15][16][17]. However, these algorithms are mainly proposed for detecting deviations of the document orientation angles from the horizontal direction or the vertical direction.…”

Section: Appl Sci 2018 8mentioning

confidence: 99%

Noncontact Surface Roughness Estimation Using 2D Complex Wavelet Enhanced ResNet for Intelligent Evaluation of Milled Metal Surface Quality

et al. 2018

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Machined surfaces are rough from a microscopic perspective no matter how finely they are finished. Surface roughness is an important factor to consider during production quality control. Using modern techniques, surface roughness measurements are beneficial for improving machining quality. With optical imaging of machined surfaces as input, a convolutional neural network (CNN) can be utilized as an effective way to characterize hierarchical features without prior knowledge. In this paper, a novel method based on CNN is proposed for making intelligent surface roughness identifications. The technical scheme incorporates there elements: texture skew correction, image filtering, and intelligent neural network learning. Firstly, a texture skew correction algorithm, based on an improved Sobel operator and Hough transform, is applied such that surface texture directions can be adjusted. Secondly, two-dimensional (2D) dual tree complex wavelet transform (DTCWT) is employed to retrieve surface topology information, which is more effective for feature classifications. In addition, residual network (ResNet) is utilized to ensure automatic recognition of the filtered texture features. The proposed method has verified its feasibility as well as its effectiveness in actual surface roughness estimation experiments using the material of spheroidal graphite cast iron 500-7 in an agricultural machinery manufacturing company. Testing results demonstrate the proposed method has achieved high-precision surface roughness estimation.

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Skew correction and line extraction in binarized printed text images

Cited by 4 publications

References 18 publications

Tesseract OCR Recognition Based on Arabic Machine-Printed Document

Tesseract OCR Recognition Based on Arabic Machine-Printed Document

An Improved Tool Wear Monitoring Method Using Local Image and Fractal Dimension of Workpiece

Noncontact Surface Roughness Estimation Using 2D Complex Wavelet Enhanced ResNet for Intelligent Evaluation of Milled Metal Surface Quality

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