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Journal articles on the topic 'Digtal Image Correlation'

Author: Grafiati

Published: 20 February 2023

Last updated: 21 February 2023

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1

Hwang, Chi Hung, Wei-Chung Wang, Yung-Hsiang Chen, and Chih-Yen Chen. "OS2-11 Multiple-Camera Semi-circular Digital Image Correlation System for Monitoring Retaining Wall(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 30. http://dx.doi.org/10.1299/jsmeatem.2015.14.30.

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2

Fujimoto, Yasuhisa, Shuichi Arikawa, Riku Yoshida, Yohei Omoto, and Satoru Yoneyama. "OS2-13 Thermal Strain Measurement of Electronic Packaging Structure Using Highly Accurate Digital Image Correlation(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 32. http://dx.doi.org/10.1299/jsmeatem.2015.14.32.

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3

Arikawa, Shuichi, Riku Yoshida, Satoru Yoneyama, Yasuhisa Fujimoto, and Yohei Omoto. "OS2-12 A Method for Eliminating Periodical Error for Highly Accurate Measurement in Digital Image Correlation(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 31. http://dx.doi.org/10.1299/jsmeatem.2015.14.31.

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4

Kang, Huimin, zhende Hou, and Cheng Yue. "OS2-15 Measurement of Bending Response of Bone in an Electric Field Using Digital Image Correlation(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 34. http://dx.doi.org/10.1299/jsmeatem.2015.14.34.

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5

Karino, Keiji, and Takuma Matsuo. "OS2-9 Non-contact Deflection Measurement for Health Monitoring of Overpass by Using Digital Image Correlation Method(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 28. http://dx.doi.org/10.1299/jsmeatem.2015.14.28.

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6

Sakaue, Kenich, Susumu Ohki, and Shinichi Suzuki. "OS2-6 Discussion on Energy Allocation problem into Branch Cracks by using Stationary Bifurcated Crack and Digital Image Correlation(Digital image correlation and its applications (2),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 25. http://dx.doi.org/10.1299/jsmeatem.2015.14.25.

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7

Chen, Terry Yuan-Fang, and Ren-Shiang Lu. "OS2-2 Development of a Hybrid Infrared Image Correlation Technique to deformation measurement of Composites(Digital image correlation and its applications (1),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 21. http://dx.doi.org/10.1299/jsmeatem.2015.14.21.

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8

Pan, Bing, and Long Tian. "OS2-8 Real-time, Non-contact and Targetless Measurement of Vertical Deflection of Bridges using Off-axis Digital Image Correlation(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 27. http://dx.doi.org/10.1299/jsmeatem.2015.14.27.

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9

Chen, Wei, Zhenyu Jiang, and Liqun Tang. "OS2-3 A Comparison of Accuracy and Convergence Capability between IC-GN Algorithm and FA-NR Algorithm in Digital Image Correlation(Digital image correlation and its applications (1),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 22. http://dx.doi.org/10.1299/jsmeatem.2015.14.22.

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10

Tan Fangxi, 谭芳喜, 肖世德 Xiao Shide, 李晟尧 Li Shengyao, and 周亮君 Zhou Liangjun. "基于密集特征匹配的数字图像相关法." Laser & Optoelectronics Progress 58, no. 16 (2021): 1612001. http://dx.doi.org/10.3788/lop202158.1612001.

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11

CHEN Liangyou, 陈梁友, and 闫浩 YAN Hao. "基于数字全息和数字图像相关方法的面内位移测量." ACTA PHOTONICA SINICA 51, no. 4 (2022): 0409002. http://dx.doi.org/10.3788/gzxb20225104.0409002.

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12

Kojima, Yuka, Hiroshi Hohjo, Takashi Ohta, and Hiroaki Makino. "OS2-14 Visualization of Non-uniform Microscopic Distribution of Thermal Strains in Glass-fiber-cloth/epoxy Laminates by Digital Image Correlation Method(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 33. http://dx.doi.org/10.1299/jsmeatem.2015.14.33.

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13

Koyama, Hiroto, and Eisaku Umezaki. "OS2-7 Behavior of Ultraviolet-Curable Resin during Curing(Digital image correlation and its applications (2),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 26. http://dx.doi.org/10.1299/jsmeatem.2015.14.26.

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14

Al-Murshedi, Sadeq, Peter Hogg, and Andrew England. "An investigation into the validity of utilising the CDRAD 2.0 phantom for optimisation studies in digital radiography." British Journal of Radiology 91, no. 1089 (September 2018): 20180317. http://dx.doi.org/10.1259/bjr.20180317.

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Objectives: To determine if a relationship exists between low contrast detail (LCD) detectability using the CDRAD 2.0 phantom, visual measures of image quality (IQ) and simulated lesion visibility (LV) when performing digital chest radiography (CXR). Methods: Using a range of acquisition parameters, a CDRAD 2.0 phantom was used to acquire a set of images with different levels of image quality. LCD detectability using the CDRAD 2.0 phantom, represented by an image quality figure inverse (IQFinv) metric, was determined using the phantom analyser software. A Lungman chest phantom was loaded with two simulated lesions, of different sizes/placed in different locations, and was imaged using the same acquisition factors as the CDRAD 2.0 phantom. A relative visual grading analysis (VGA) was used by seven observers for IQ and LV evaluation of the Lungman images. Correlations between IQFinv, IQ and LV were investigated. Results: Pearson’s correlation demonstrated a strong positive correlation (r = 0.91; p < 0.001) between the IQ and the IQFinv. Spearman’s correlation showed a good positive correlation (r = 0.79; p < 0.001) and (r = 0.68; p < 0.001) between the IQFinv and the LV for the first lesion (left upper lobe) and the second lesion (right middle lobe), respectively. Conclusions: From results presented in this study, the automated evaluation of LCD detectability using CDRAD 2.0 phantom is likely to be a suitable option for IQ and LV evaluation in digital CXR optimisation studies. Advances in knowledge: This research establishes the potential of the CDRAD 2.0 phantom in digital CXR optimisation studies.

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15

Shin, Bumshick, and KyuHan Kim. "Analysis of Wave-Induced Current Using Digital Image Correlation Techniques." Journal of Sensors 2018 (2018): 1–6. http://dx.doi.org/10.1155/2018/1784507.

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Recently, advancement of digital image techniques and communications technology has enabled the application of existing images for scientific purposes. Furthermore, both quantitative and qualitative analyses of images have become possible through image processing such as transmit/storage of digital image data and image rectification. In this study, a coast having representative characteristics of east coast of Korea was selected with having erosion in winter, and the sedimentation in summer takes place repeatedly. Three-dimensional hydraulic model test was conducted to analyze its outcomes by a digital image correlation technique in order to understand the wave-induced current affecting the sediment transport. For this study, images filmed by the high-sensitive and high-resolution video camera were converted into stopped images of regular intervals and then those converted images were used for the following procedure to analyze flow and velocity into digital coordinates. The outcomes from interpretation of images filmed by the high-sensitive and high-resolution video camera can be utilized as a very useful analysis method for appreciating the generation mechanism and movement route of longshore current and rip current.

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16

McCormick, Nick, and Jerry Lord. "Digital Image Correlation." Materials Today 13, no. 12 (December 2010): 52–54. http://dx.doi.org/10.1016/s1369-7021(10)70235-2.

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17

Wilson, Anthony J., Bianca C. Chin, Vivian M. Hsu, Michael N. Mirzabeigi, and Ivona Percec. "Digital Image Correlation." Plastic and Reconstructive Surgery 135, no. 5 (May 2015): 869e—876e. http://dx.doi.org/10.1097/prs.0000000000001224.

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18

Forsey, A., and S. Gungor. "Demosaicing images from colour cameras for digital image correlation." Optics and Lasers in Engineering 86 (November 2016): 20–28. http://dx.doi.org/10.1016/j.optlaseng.2016.05.006.

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19

Uchino, Masakazu. "OS01W0200 Sub-micron displacement measurement using a digital image correlation method." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2003.2 (2003): _OS01W0200. http://dx.doi.org/10.1299/jsmeatem.2003.2._os01w0200.

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20

Chen, Lin, Rong Sheng Lu, Yan Qiong Shi, and Jian Sheng Tian. "A Differential Evolution Stereo Matching Method in Digital Image Correlation." Key Engineering Materials 625 (August 2014): 297–304. http://dx.doi.org/10.4028/www.scientific.net/kem.625.297.

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Stereo matching is widely used in three-dimensional (3D) reconstruction, stereo machine vision and digital image correlation. The aim of stereo matching process is to solve the well-known correspondence problem, which tries to match points or features from one image with the same points or features in another image from the same 3D scene. There are two basic ways, correlation-based and feature-based, are used to find the correspondences between two images. The correlation-based way is to determine if one location in one image looks/seems like another in another image, and the feature-based way to find if a subset of features in one image is similar in the another image. In stereo matching, a simple algorithm is to compare small patches between two rectified images by correlation search. For the pair images acquired from two cameras inevitably exists some rotation transformation, the algorithm first runs a preprocessing step to rectify the images with the epipolar rectification to simplify the problem of finding matching points between images. The epipolar rectification is to determine a transformation of each image plane such that pairs of conjugate epipolar lines become collinear and parallel to one of the image axes. It will lead the loss of gray information of images. The effect is dependent on the amount of angle. When the angle is big enough, the correlation search may yield error results because of retrograded correlation effect. In order to solve the problem, the paper presents an improved stereo matching algorithm with differential evolution to solve the correspondence problem. Our method doesn’t need to runs the preprocessing step to rectify the images with the epipolar rectification. It uses a differential evolution algorithm to minimize the correlation function which contains the angle information after acquiring the epipoar geometry constraint of two image pairs. Then it utilizes a flood-fill algorithm to search correspondence sub-region in the area around the epipolar line. The flood-fill algorithm can overcome the problem of the traditional row-column scanning search method, which will encounter boundary barrier where exists concave polygons or cavities. The Experimental results show that the proposed method can be easily implemented in stereo matching without loss of information of image features with large rotation angle transformation. In the paper, we will introduce the stereo matching principle and its algorithms, including the differential evolution algorithm for finding the correspondences with large rotation transformation between stereo image pairs and the flood-fill traversal strategy for matching large area with complex concave polygons or cavities. In the end of the paper, some experimental results will be given to illustrate the method effectiveness. Keywords: digital image correlation, stereo matching algorithm, epipolar geometry, flood fill algorithm, differential evolution, rotation angle

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21

Chen, Jiangping, and Weijun Tao. "Gradient-Based Automatic Exposure Control for Digital Image Correlation." Sustainability 15, no. 2 (January 7, 2023): 1149. http://dx.doi.org/10.3390/su15021149.

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Digital image correlation (DIC) is widely used in material experiments such as ores; the quality of a speckle image directly affects the accuracy of the DIC calculation. This study aims to acquire high-quality speckle pattern images and improve the calculation accuracy and stability. A gradient-based image quality metric was selected to evaluate the image quality, and its validity was verified by a rigid body experiment and a numerical experiment. Based on the maximum image quality metric, an automatic exposure control algorithm and the control procedure were proposed to obtain the optimal exposure time. Finally, nine sets of images with different poses and illuminations were captured, and displacement and strain fields were calculated at the fixed exposure time and the optimized exposure time. The results of the rigid-body motion experiment show that the calculated data at the optimized exposure time is smoother and less noisy, and the error is smaller, which verifies the effectiveness of the exposure control procedure and its algorithm and improves the accuracy and stability of DIC calculation.

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22

Jia, Zhaoyang, and Guangxue Chen. "Study on Digital Image Inpainting Method Based on Multispectral Image Decomposition Synthesis." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 01 (October 11, 2018): 1954004. http://dx.doi.org/10.1142/s0218001419540041.

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The paper analyzes the image inpainting problem of damaged Painting Arts for high fidelity images reproduction, and a digital image inpainting method based on multispectral image decomposition synthesis is proposed. Firstly, multi-channel images of Painting Arts are obtained by multispectral technology. Then, a polynomial regression method based on principal component is used to reconstruct the spectral image. The reconstructed image is decomposed by VO image decomposition model. During the inpainting process, the channel correlation of the structure image and the texture image of multispectral image is effectively removed. The digital image inpainting is performed respectively. Finally, the digital inpainted image is obtained by synthesis. The experimental results show that the digital image inpainting based on multispectral image decomposition synthesis reduces the problem of low image inpainting accuracy caused by the correlation between the color components in the traditional digital image inpainting process, and reduces the mismatch of the inpainting image. Appearance of pseudo color of inpainting image is reduced. MSE of multispectral images inpainting qualities is 2.7951 and PSNR of multispectral images inpainting qualities is 44.1681, so it is superior to traditional image inpainting algorithm. It provides a reliable basis for digital inpainting, digital archives and high fidelity replication of defective Painting Arts.

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23

Khaja, Abdul Aziz, and Wael A. Samad. "Hybrid Digital Image Correlation." Journal of Engineering Mechanics 146, no. 4 (April 2020): 04020009. http://dx.doi.org/10.1061/(asce)em.1943-7889.0001726.

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24

Xie, Huimin, and Yilan Kang. "Digital image correlation technique." Optics and Lasers in Engineering 65 (February 2015): 1–2. http://dx.doi.org/10.1016/j.optlaseng.2014.07.010.

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25

Ge Pengxiang, 葛朋祥, 王欢庆 Wang Huanqing, 朱奕磊 Zhu Yilei, and 王永红 Wang Yonghong. "基于平面镜成像的单相机数字图像相关三维全景测量." Chinese Journal of Lasers 49, no. 9 (2022): 0904004. http://dx.doi.org/10.3788/cjl202249.0904004.

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26

Pan Jiyu, 潘济宇, 张水强 Zhang Shuiqiang, 苏志龙 Su Zhilong, 武珅 Wu Shen, and 张东升 Zhang Dongsheng. "基于数字图像相关的水下螺旋桨三维变形测量." Acta Optica Sinica 41, no. 12 (2021): 1212001. http://dx.doi.org/10.3788/aos202141.1212001.

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27

Li Guihua, 李桂华, 马万龙 Ma Wanlong, 朱天天 Zhu Tiantian, 付中男 Fu Zhongnan, and 葛朋祥 Ge Pengxiang. "基于数字图像相关方法的空心圆盘热变形测量." Laser & Optoelectronics Progress 58, no. 14 (2021): 1412003. http://dx.doi.org/10.3788/lop202158.1412003.

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28

Yoshioka, Tomohiko, Yasuyuki Morita, Mitsugu Todo, Yasuyuki Matsusita, and Kazuo Arakawa. "P-19 Deformation Analysis of Periodontal Tissue using Digital Image Correlation Analysis." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2007.3 (2007): S107. http://dx.doi.org/10.1299/jsmeapbio.2007.3.s107.

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29

Goda, Hiroki, Yuichiro Kawabata, Masakazu Uchino, and Makoto Hibino. "OS01F084 Local Deformation Characteristics of Concrete Measured by Digital Image Correlation Method." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2011.10 (2011): _OS01F084——_OS01F084—. http://dx.doi.org/10.1299/jsmeatem.2011.10._os01f084-.

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30

Wang, Zhuoyi, Dan Tulpan, and Renee Bergeron. "PSI-16 Estimation of pigs live body weight from digital images using reference objects." Journal of Animal Science 99, Supplement_3 (October 8, 2021): 276–77. http://dx.doi.org/10.1093/jas/skab235.507.

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Abstract The live body weight (LBW) is an important parameter providing guidance for estimation of growth and feed conversion efficiency, body condition, presence of disease, and management of housing, nutrition and animal health in different life stages of livestock. This research study explores the possibility of developing a semi-automatic analytic system that estimates the LBW of pigs by applying machine learning methods that use approximated biometric measurements extracted from digital images acquired with consumer-level cameras in the presence of a reference object. Images corresponding to 12 pigs were sampled on two different dates 1 month apart and acquired using a consumer-level Motorola X4 mobile phone. The best 3 images for each pig were selected for each time point. Six measurements were extracted from each image using ImageJ. A total of 72 data points were analyzed using RStudio, and the generated correlation plot confirmed the positive correlations between the 6 predictors and LBW. Five machine learning (ML) methods were used to model the dependency between the measured parameters and LBW using WEKA. The Random Forest model outperformed all the other models and predicted LBW with the highest prediction accuracy (97%) and the lowest prediction error (MAE = 6.54), which could represent a good candidate for further studies. In conclusion, the semi-automatic image-based system is a promising approach combining machine learning, digital image analysis and manual scale extraction with the aid of reference objects of known size for accurate pig LBW estimation. The next stage of this study aims to integrate automatic image acquisition and image processing solutions in the current approach. This novel system will be cost- and time-efficient, and it can contribute to the development of intelligent solutions for scientific research and enhancing animal productivity in commercial pig farms.

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31

Okaniwa, Yumi, Jun Koyanagi, Masahiro Hojo, Ippei Susuki, and Satoru Yoneyama. "OS2-5 Stress-concentration Interaction of Two Neighboring Cracks Evaluated by DIC and XFEM(Digital image correlation and its applications (2),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 24. http://dx.doi.org/10.1299/jsmeatem.2015.14.24.

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32

Lin, Zhe, Tian Cai, and Yanfeng Wang. "Parallel reliability-guided algorithm for digital image correlation." Insight - Non-Destructive Testing and Condition Monitoring 61, no. 12 (December 1, 2019): 729–37. http://dx.doi.org/10.1784/insi.2019.61.12.729.

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Digital image correlation is a non-contact optical method for measuring the displacement and strain on the surface of a material. The existing reliability-guided digital image correlation (RG-DIC) method is stable and reliable for a single image but it still needs a large calculational resource for a sequence of images. Due to the decorrelation effect, the reference image must be replaced several times to correct the measurement results for an image sequence involving a large deformation or a discontinuous deformation. Since the process must be executed sequentially, image by image, the total time required is often unacceptably large when the image sequence is long. The challenge is to find a way of improving the speed while retaining calculational reliability and measurement accuracy, which are important for the practical application of DIC. To address this problem, an improved method is proposed in this paper. The parallel bottleneck caused by the decorrelation effect is solved through improving the parallelism to increase the processing speed. This approach can be used to calculate the strain field of the surface of the material in cases of discontinuous deformation, such as in the area near to a crack. Compared with existing methods, this method not only retains the calculational reliability but also greatly improves calculation speed, especially on current multi-core computing platforms.

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33

Kim, Sung-Wan, and Nam-Sik Kim. "Multi-point Dynamic Displacement Measurements of Structures Using Digital Image Correlation Technique." Journal of the Earthquake Engineering Society of Korea 13, no. 3 (June 30, 2009): 11–19. http://dx.doi.org/10.5000/eesk.2009.13.3.011.

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34

Goda, Hiroki, Yuichiro Kawabata, and Masakazu Uchino. "OS2-10 Evaluation on Expansion Characteristics of Concrete by Stick Scanner and Stress Release Method(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 29. http://dx.doi.org/10.1299/jsmeatem.2015.14.29.

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35

Crammond, G., S. W. Boyd, and Janice M. Dulieu-Barton. "Speckle Pattern Characterisation for High Resolution Digital Image Correlation." Applied Mechanics and Materials 70 (August 2011): 261–66. http://dx.doi.org/10.4028/www.scientific.net/amm.70.261.

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Digital image correlation (DIC) is an optical technique for full field deformation measurement. The spatial resolution and precision of the measurements are limited by the number of pixels within the image. The use of magnifying optics provides greater spatial resolution images, enabling smaller displacements to be observed with greater accuracy. Increasing the magnification of an image significantly changes the appearance of the non-periodic, stochastic speckle pattern which provides the grey scale contrast necessary for the image correlation method. In the paper a methodology is developed to evaluate the properties of different speckle pattern types under a range of resolutions up to 705 pixel / mm. Numerical deformation of the patterns is also undertaken to evaluate how the changes in the pattern properties affect the accuracy of the DIC measurements.

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Du Jianxin, 杜鉴昕, 赵加清 Zhao Jiaqing, 王海涛 Wang Haitao, 孙立斌 Sun Libin, and 吴莘馨 Wu Xinxin. "针对裂尖变形场测量的包络单元局部数字图像相关方法." Acta Optica Sinica 42, no. 1 (2022): 0112003. http://dx.doi.org/10.3788/aos202242.0112003.

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37

Vaitkunas, Tomas, Paulius Griskevicius, and Adi Adumitroaie. "Peridynamic Approach to Digital Image Correlation Strain Calculation Algorithm." Applied Sciences 12, no. 13 (June 28, 2022): 6550. http://dx.doi.org/10.3390/app12136550.

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Digital image correlation is an experimental optical non-contact full field displacement and strain evaluation method based on the surface subsets tracking with photo cameras, digital images processing, and numerical computation. However, the full field of strain computation is a challenging problem, mainly because the displacement field to be differentiated is not continuous, individual subsets are tracked by the optical digital image correlation system. Moreover, the numerical differentiation can also amplify the noise of the displacement field inducing thus strain errors when the displacement data are poor. The peridynamics theory (which equations are cast in terms of spatial integrals of displacements, instead of spatial derivatives in the classical continuum mechanics) based algorithm is considered in this study and applied for the experimental digital image correlation displacement field to analyze possible peridynamic differentiation method advantages. A strains convergence analysis between the digital image correlation and peridynamic differentiation methods is done in this study. The integro-differential strain calculation as an alternative method is validated against digital image correlation and finite element simulation strain fields. It is also shown that the digital image correlation, a noisy displacement field, still provides an accurate and low level noise strain evaluation based on the proposed method.

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38

Sjödahl, Mikael. "Gradient Correlation Functions in Digital Image Correlation." Applied Sciences 9, no. 10 (May 24, 2019): 2127. http://dx.doi.org/10.3390/app9102127.

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The performance of seven different correlation functions applied in Digital Image Correlation has been investigated using simulated and experimentally acquired laser speckle patterns. The correlation functions were constructed as combinations of the pure intensity correlation function, the gradient correlation function and the Hessian correlation function, respectively. It was found that the correlation function that was constructed as the product of all three pure correlation functions performed best for the small speckle sizes and large correlation values, respectively. The difference between the different functions disappeared as the speckle size increased and the correlation value dropped. On average, the random error of the combined correlation function was half that of the traditional intensity correlation function within the optimum region.

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Chou, Ming-Chung. "Evaluation of Non-Uniform Image Quality Caused by Anode Heel Effect in Digital Radiography Using Mutual Information." Entropy 23, no. 5 (April 25, 2021): 525. http://dx.doi.org/10.3390/e23050525.

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Anode heel effects are known to cause non-uniform image quality, but no method has been proposed to evaluate the non-uniform image quality caused by the heel effect. Therefore, the purpose of this study was to evaluate non-uniform image quality in digital radiographs using a novel circular step-wedge (CSW) phantom and normalized mutual information (nMI). All X-ray images were acquired from a digital radiography system equipped with a CsI flat panel detector. A new acrylic CSW phantom was imaged ten times at various kVp and mAs to evaluate overall and non-uniform image quality with nMI metrics. For comparisons, a conventional contrast-detail resolution phantom was imaged ten times at identical exposure parameters to evaluate overall image quality with visible ratio (VR) metrics, and the phantom was placed in different orientations to assess non-uniform image quality. In addition, heel effect correction (HEC) was executed to elucidate the impact of its effect on image quality. The results showed that both nMI and VR metrics significantly changed with kVp and mAs, and had a significant positive correlation. The positive correlation is suggestive that the nMI metrics have a similar performance to the VR metrics in assessing the overall image quality of digital radiographs. The nMI metrics significantly changed with orientations and also significantly increased after HEC in the anode direction. However, the VR metrics did not change significantly with orientations or with HEC. The results indicate that the nMI metrics were more sensitive than the VR metrics with regards to non-uniform image quality caused by the anode heel effect. In conclusion, the proposed nMI metrics with a CSW phantom outperformed the conventional VR metrics in detecting non-uniform image quality caused by the heel effect, and thus are suitable for quantitatively evaluating non-uniform image quality in digital radiographs with and without HEC.

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40

Yang, J., and K. Bhattacharya. "Combining Image Compression with Digital Image Correlation." Experimental Mechanics 59, no. 5 (January 18, 2019): 629–42. http://dx.doi.org/10.1007/s11340-018-00459-y.

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41

Neggers, J., B. Blaysat, J. P. M. Hoefnagels, and M. G. D. Geers. "On image gradients in digital image correlation." International Journal for Numerical Methods in Engineering 105, no. 4 (July 14, 2015): 243–60. http://dx.doi.org/10.1002/nme.4971.

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42

Farias, C. B. M., A. Arrolho, M. C. M. Silva, R. R. Cruz, L. P. N. Ramos, and S. A. M. Souza. "Estimation and analysis of particles from seeds of maximiliana maripa (aubl.) drude (arecaceae)." Scientific Electronic Archives 13, no. 10 (September 30, 2020): 28. http://dx.doi.org/10.36560/131020201056.

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Abstract:

The present work aims to estimate the length and width of the seeds, through the analysis of digital images and to validate the methodology through statistical data. To estimate the length and width of seeds via image analysis, 50 M.maripa seeds were used. The seeds were arranged in a decreasing way from 1 to 25 diagonally, on a matte black fabric, on a phenotyping platform, with a Sony Hd Avchd progressive digital Gps camera, coupled at a height of 50 cm. The images were captured by the camera in automatic mode, without flash, automatic ISO speed, in an RGB system and with a size above 2Mb. Soon after the seeds passed the traditional evaluation method with the aid of a digital caliper, measured in terms of length and width. The images were analyzed with the ImageJ software. Statistical analyzes were performed with the aid of the Sigmaplot program. The results of the length and width of the seeds of Inajá seen by the caliper and digital image via camera, were very distant, showing high dispersion and low correlation r = 0.4037 and R² = 0.1629 for length and r = 0.2985 and R² = 0.0891, showing that the Compared data had little similarity. The error between both the methodology was considered low: 3,81063 and 3,769 for the variables of seed length and width. The method of analysis by digital image and caliper for estimating the length and width of Maximiliana maripa seeds showed a low correlation between the two methodologies. The use of image analysis to estimate the length and width of M. maripa seeds is not indicated.

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Then, P., and Y. C. Wang. "PERCEIVING DIGITAL WATERMARK DETECTION AS IMAGE CLASSIFICATION PROBLEM." Journal of IT in Asia 2, no. 1 (April 26, 2016): 1–22. http://dx.doi.org/10.33736/jita.52.2007.

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Digital watermark detection is treated as classification problem of image processing. For image classification that searches for a butterfly, an image can be classified as positive class that is a butterfly and negative class that is not a butterfly. Similarly, the watermarked and unwatermarked images are perceived as positive and negative class respectively. Hence, Support Vector Machine (SVM) is used as the classifier of watermarked and unwatermarked digital image due to its ability of separating both linearly and non-linearly separable data. Hyperplanes of various detectors are briefly elaborated to show how SVM's hyperplane is suitable for Stirmark attacked watermarked image. Cox’s spread spectrum watermarking scheme is used to embed the watermark into digital images. Then, Support Vector Machine is trained with both the watermarked and unwatermarked images. Training SVM eliminates the use of watermark during the detection process. Receiver Operating Characteristics (ROC) graphs are plotted to assess the false positive and false negative probability of both the correlation detector of the watermarking schemes and SVM classifier. Both watermarked and unwatermarked images are later attacked under Stirmark, and then tested on the correlation detector and SVM classifier. Remedies are suggested to preprocess the training data. The optimal setting of SVM parameters is also investigated and determined besides preprocessing. The preprocessing and optimal parameters setting enable the trained SVM to achieve substantially better results than those resulting from the correlation detector.

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44

Sadeq, Haval. "Using Total Probability in Image Template Matching." International Arab Journal of Information Technology 17, no. 3 (December 1, 2019): 347–57. http://dx.doi.org/10.34028/iajit/17/3/8.

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Image template matching is a main task in photogrammetry and computer vision. The matching can be used to automatically determine the 3D coordinates of a point. A firstborn image matching method in fields of photogrammetry and computer vision is area-based matching, which is based on correlation measuring that uses normalised cross-correlation. However, this method fails at a discontinuous edge and at the area of low illumination or at geometric distortion because of changes in imaging location. Thus, these points are considered outliers. The proposed method measures correlations, which is based on normalised cross-correlation, at each point by using various sizes of window and then considering the probability of correlations for each window. Thereafter, the determined probability values are integrated. On the basis of a specific threshold value, the point of maximum total probability correlation is recognised as a corresponding point. The algorithm is applied to aerial images for Digital Surface Model (DSM) generation. Results show that the corresponding points are identified successfully at different locations, especially at a discontinuous point, and that a Digital Surface Model of high resolution is generated.

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Wentzell, Scott, Robert Sterling Nesbitt, James Macione, and Shiva Kotha. "Measuring strain using digital image correlation of second harmonic generation images." Journal of Biomechanics 46, no. 12 (August 2013): 2032–38. http://dx.doi.org/10.1016/j.jbiomech.2013.06.003.

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Tomičevć, Zvonimir, François Hild, and Stéphane Roux. "Mechanics-aided digital image correlation." Journal of Strain Analysis for Engineering Design 48, no. 5 (June 11, 2013): 330–43. http://dx.doi.org/10.1177/0309324713482457.

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Shen, Huan, Peize Zhang, and Xiang Shen. "Kernel based Digital Image Correlation." International Journal of Signal Processing, Image Processing and Pattern Recognition 8, no. 3 (March 31, 2015): 261–72. http://dx.doi.org/10.14257/ijsip.2015.8.3.24.

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Yang, J., and K. Bhattacharya. "Augmented Lagrangian Digital Image Correlation." Experimental Mechanics 59, no. 2 (December 6, 2018): 187–205. http://dx.doi.org/10.1007/s11340-018-00457-0.

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Mudassar, Asloob Ahmad, and Saira Butt. "Improved Digital Image Correlation method." Optics and Lasers in Engineering 87 (December 2016): 156–67. http://dx.doi.org/10.1016/j.optlaseng.2015.10.002.

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Curt, J., M. Capaldo, F. Hild, and S. Roux. "Optimal digital color image correlation." Optics and Lasers in Engineering 127 (April 2020): 105896. http://dx.doi.org/10.1016/j.optlaseng.2019.105896.

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