Exploring Image Binarization Techniques

Chaki, Nabendu; Shaikh, Soharab Hossain; Saeed, Khalid

doi:10.1007/978-81-322-1907-1

Cited by 52 publications

(18 citation statements)

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“…[17,22,53]) and those focused on thresholdbased methods [47,60] to more recent surveys-from the overall (see e.g. [11,32,56,68,69]), to those focused on image binarization [9,58], thresholding [21,52], or colour image segmentation [55].…”

Section: A Brief Review On Image Segmentation Methodsmentioning

confidence: 99%

Uncertainty Estimation for Ultrasonic Inspection of Composite Aerial Structures

et al. 2019

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Components made of polymeric composite materials, such as wings and stabilizers of aircrafts, are periodically inspected using non-destructive testing methods. Ultrasonic testing is one of the primary inspection methods applied in the aircraft/aerospace industry. Image processing methods have been developed for the purpose of ultrasonic data analysis and increasing the inspection efficiency. A critically important factor in damage sizing is appropriate processing of ultrasonic data in order to extract the damage region properly before calculation of its extent. The paper presents a comparative analysis of various image segmentation methods in the light of accuracy of damage detection in ultrasonic C-Scans of composite structures. A brief review of image segmentation methods is presented and their usefulness in the ultrasonic testing applications is discussed. The selected methods, namely the threshold-, edge-, region-, and clustering-based ones, were tested using ultrasonic C-Scans of a specimen with barely visible impact damage and aircraft panels with delamination, all made of CFRP composites. A problem with the selection of appropriate input parameters using most of the segmentation methods is discussed, and non-parametric histogram-based approaches are proposed. A quantitative analysis of the accuracy of damage detection using the segmentation methods is presented and the most suitable approaches are introduced. The proposed processing procedures may significantly improve the objectivity of inspections of composite elements and structures using ultrasonic testing.

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Section: A Brief Review On Image Segmentation Methodsmentioning

confidence: 99%

Uncertainty Estimation for Ultrasonic Inspection of Composite Aerial Structures

et al. 2019

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“…The text pixels will be given a white color with a v alue of "1" and background pixels are black with a value of "0" [7]. Otsu's method is used to binarize a grayscale input image.…”

Section: A Preprocessingmentioning

confidence: 99%

Latin Letters Recognition Using Optical Character Recognition to Convert Printed Media Into Digital Format

Anugrah

Bintoro

2017

indones.j.electron.telecommun.

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Printed media is still popular in nowadays society. Unfortunately, such media encountered several drawbacks. For example, this type of media consumes large storage that impact in high maintenance cost. To keep printed information more efficient and long-lasting, people usually convert it into digital format. In this paper, we built Optical Character Recognition (OCR) system to enable automatic conversion the image containing the sentence in Latin characters into digital text-shaped information. This system consists of several interrelated stages including preprocessing, segmentation, feature extraction, classifier, model and recognition. In preprocessing, the median filter is used to clarify the image from noise and the Otsu's function is used to binarize the image. It followed by character segmentation using connected component labeling. Artificial neural network (ANN) is used for feature extraction to recognize the character. The result shows that this system enable to recognize the characters in the image whose success rate is influenced by the training of the system.

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“…Chaki et al [1] introduced a detailed survey about the principles of image binarization techniques. Gill [2] evaluated the different image binarization techniques to find the gaps in existing ones.…”

Section: Related Workmentioning

confidence: 99%

Accurate, Fast and Noiseless Image Binarization

Al-Khawand

Kadry

Bozzo³

et al. 2016

Stat., optim. inf. comput.

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In this paper, we present an accurate, swift and noiseless image binarization technique that was tested on real life back side container images. Our approach consists of transferring a colored image into grayscale, then to construct the histogram which will be divided into group of colors and after that, the foreground -that can be darker or lighter than the background-will be automatically identified and finally, the foreground boundaries will be assiduously enhanced before creating the binarized image. The average processing time of our proposed method is less than 8 milliseconds which makes it highly suitable for real life multi-user applications.

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Exploring Image Binarization Techniques

Cited by 52 publications

References 0 publications

Uncertainty Estimation for Ultrasonic Inspection of Composite Aerial Structures

Uncertainty Estimation for Ultrasonic Inspection of Composite Aerial Structures

Latin Letters Recognition Using Optical Character Recognition to Convert Printed Media Into Digital Format

Accurate, Fast and Noiseless Image Binarization

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