scholarly journals EVALUATION OF CRACK WIDTH DISTRIBUTION CHARACTERISTICS OF RC WALL USING IMAGE PROCESSING

2021 ◽  
Vol 86 (781) ◽  
pp. 481-489
Author(s):  
Yizhe WANG ◽  
Noriyuki TAKAHASHI
Keyword(s):  
Image Processing ◽  
Crack Width ◽  
Distribution Characteristics ◽  
Width Distribution

scholarly journals Method for Assessment of Changes in the Width of Cracks in Cement Composites with Use of Computer Image Processing and Analysis

2017 ◽  
Vol 39 (2) ◽  
pp. 73-80 ◽  
Author(s):  
Kamil Tomczak ◽  
Jacek Jakubowski ◽  
Przemysław Fiołek
Keyword(s):  
Image Processing ◽  
Crack Width ◽  
Healing Process ◽  
Cement Composites ◽  
Self Healing ◽  
Initial Image ◽  
Scale Invariant ◽  
Line Segments ◽  
Changes Over Time ◽  
Over Time

Abstract Crack width measurement is an important element of research on the progress of self-healing cement composites. Due to the nature of this research, the method of measuring the width of cracks and their changes over time must meet specific requirements. The article presents a novel method of measuring crack width based on images from a scanner with an optical resolution of 6400 dpi, subject to initial image processing in the ImageJ development environment and further processing and analysis of results. After registering a series of images of the cracks at different times using SIFT conversion (Scale-Invariant Feature Transform), a dense network of line segments is created in all images, intersecting the cracks perpendicular to the local axes. Along these line segments, brightness profiles are extracted, which are the basis for determination of crack width. The distribution and rotation of the line of intersection in a regular layout, automation of transformations, management of images and profiles of brightness, and data analysis to determine the width of cracks and their changes over time are made automatically by own code in the ImageJ and VBA environment. The article describes the method, tests on its properties, sources of measurement uncertainty. It also presents an example of application of the method in research on autogenous self-healing of concrete, specifically the ability to reduce a sample crack width and its full closure within 28 days of the self-healing process.

scholarly journals Analysis of Fine Crack Images Using Image Processing Technique and High-Resolution Camera

2021 ◽  
Vol 11 (20) ◽  
pp. 9714
Author(s):  
Hoseong Jeong ◽  
Baekeun Jeong ◽  
Myounghee Han ◽  
Dooyong Cho
Keyword(s):  
Image Processing ◽  
Crack Width ◽  
Focal Length ◽  
Great Influence ◽  
Health And Safety ◽  
Digital Camera ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Width Measurement ◽  
Working Distance

Visual inspections are performed to investigate cracks in concrete infrastructure. These activities require manpower or equipment such as articulated ladders. Additionally, there are health and safety issues because some structures have low accessibility. To deal with these problems, crack measurement with digital images and digital image processing (DIP) techniques have been adopted in various studies. The objective of this experimental study is to evaluate the optical limit of digital camera lenses as working distance increases. Three different lenses and two digital cameras were used to capture images of lines ranging from 0.1 to 0.5 mm in thickness. As a result of the experiments, it was found that many elements affect width measurement. However, crack width measurement is dependent on the measured pixel values. To accurately measure width, the measured pixel values must be in decimal units, but that is theoretically impossible. According to the results, in the case of 0.3 mm wide or wider cracks, a working distance of 1 m was secured when the focal length was 50 mm, and working distances of 3 m and 4 m were secured when the focal length was 100 mm and 135 mm, respectively. However, for cracks not wider than 0.1 mm, focal lengths of 100 mm and 135 mm showed measurability within 1 m, but a focal length of 50 mm was judged to hardly enable measurement except for certain working positions. Field measurement tests were conducted to verify measurement parameters identified by the results of the indoor experiment. The widths of actual cracks were measured through visual inspection and used for the analysis. From the evaluation, it was confirmed that the number of pixels corresponding to the working distance had a great influence on crack width measurement accuracy when using image processing. Therefore, the optimal distance and measurement guidelines required for the measurement of the size of certain objects was presented for the imaging equipment and optical equipment applied in this study.

Rapid detection of building cracks based on image processing technology with double square artificial marks

2018 ◽  
Vol 22 (5) ◽  
pp. 1186-1193 ◽  
Author(s):  
Gang Yang ◽  
Jianchao Wu ◽  
Qing Hu
Keyword(s):  
Image Processing ◽  
Crack Width ◽  
Processing Technique ◽  
Processing Technology ◽  
Image Processing Technique ◽  
Actual Length ◽  
Image Processing Technology ◽  
Operating Environments ◽  
Hours Of Work ◽  
Calculation Results

In order to measure the crack width of dangerous buildings quickly and accurately, this article presents a new crack width measurement method, which is based on image processing technology, using double square artificial markers to identify building cracks and calculate crack width. It makes two 10 mm × 10 mm black square artificial marks and places them near the sides of the crack. Then it uses a camera to collect crack images and transfer photos to a computer. The crack image is subjected to image graying, binarization, denoising, image segmentation, and pixel calibration based on the image processing technique. Finally, the actual length value of the unit pixel is calculated. Then it can calculate the actual width of the crack according to the number of pixels included in the test crack. The calculation results show that the accuracy of the proposed method is 98.56% compared with the measured data. The calculation method can accurately and effectively detect the crack width of dangerous buildings and improve work efficiency. At the same time, it can avoid long hours of work in dangerous operating environments.

The Algorithm to Measure Crack Width with Incircle

2013 ◽  
Vol 684 ◽  
pp. 481-485 ◽  
Author(s):  
Bao Zhen Ge ◽  
Qi Jun Luo ◽  
Bin Ma ◽  
Yong Jie Wei ◽  
Bo Chen ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Crack Width ◽  
Experimental Results ◽  
Average Width ◽  
Center Of A Group ◽  
Major Defect ◽  
Skeleton Point

Crack is a major defect of buildings. Digital image methods are often used to detect cracks. But incorrect or un-unique results may be inverted with an inappropriate algorithm. An image processing way is presented to obtain the sole width value. Meanwhile, the crack with several branches can be measured. In the processing, the crack skeleton is first calculated. Then each of the points on the skeleton is served as a center of a group of circles, one by one. The radius of the circles is increased step by step. The iterations will not stop until any point in the circle goes out of the crack. Thus the last circle in the iteration is served as an incircle of the crack. The diameter of the incircle is a crack width in a given skeleton point. The maximal and average width of the crack will be calculated after all the incircles with all the skeleton point are traversed. The experimental results show the proposed method can extract the width of cracks in a complex context.

scholarly journals Construction of Concrete Surface Crack Recognition Model Based on Digital Image Processing Technology

2021 ◽  
Vol 2074 (1) ◽  
pp. 012067
Author(s):  
Yuzhong Kang ◽  
Aimin Yu ◽  
Wenquan Zeng
Keyword(s):  
Image Processing ◽  
Prestressed Concrete ◽  
Crack Width ◽  
Crack Detection ◽  
Concrete Surface ◽  
Concrete Bridges ◽  
Crack Identification ◽  
Detection Accuracy ◽  
Depth Analysis ◽  
Class B

Abstract In this paper, the bridge crack detection method based on digital images is studied. In-depth analysis and evaluation are performed on the image processing algorithms such as image graying, resolution of checkerboard corner pixel rate, filtering denoising, and edge detection, etc. The calculation and software system for bridge crack width based on videos (or images) is implemented, and 15 bridge crack images are used to verify its crack detection accuracy. The results suggest that the proposed crack identification method in this paper can be used for the crack detection of reinforced concrete bridges and class B prestressed concrete bridges properly. When the crack width is greater than 0.3 mm, the calculated crack width value based on images is very close to the measured value.

scholarly journals Study of Cavitation and Cavitation Erosion Quantitative Method Based on Image Processing Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Dongli Lv ◽  
Zhanghua Lian ◽  
Tao Zhang
Keyword(s):  
Image Processing ◽  
Cavitation Erosion ◽  
Processing Technique ◽  
Processing Method ◽  
Image Processing Technique ◽  
Distribution Characteristics ◽  
Airfoil Surface ◽  
Image Processing Method ◽  
Hydraulic Machinery ◽  
Cavitation Behavior

Cavitation erosion on the wetted surface of hydraulic machinery is directly related to the cavitation behavior. In this paper, the cavitation behavior and cavitation erosion characteristics on the airfoil surface were observed experimentally, and then, image processing methods for quantifying cavitation structure and cavitation erosion were established. Laser-CCD system was used to obtain the cavitation structure on the airfoil surface and the microtopographies of the cavitation erosion at different magnifications were obtained by SEM. The distribution and shape of cavitation pits were analyzed. An image processing method based on statistical principle was used to analyze the distribution characteristics of the cavitation structure. The mean and mean square value of the cavitation structure were obtained. The average volume and the volume change rate of cavitation cloud in each position of the flow field during a cavitation period were described. According to the characteristics of cavitation pits, an image processing method based on background correction, edge detection, and binary morphology processing was established, and then, the distribution characteristics and the area of the cavitation pits were obtained. Finally, the effectiveness of the methods is verified by the image processing of cavitation pit in different locations on the hydrofoil.

scholarly journals Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

2019 ◽  
Vol 4 (2) ◽  
pp. 19 ◽  
Author(s):  
Dorafshan ◽  
Thomas ◽  
Maguire
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Frequency Domain ◽  
Crack Width ◽  
Crack Detection ◽  
Spatial Domain ◽  
Gaussian Filter ◽  
Laplacian Of Gaussian Filter ◽  
Image Processing Algorithms ◽  
Processing Algorithms

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare different edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS.

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