Quality assessment of speckle patterns for digital image correlation by Shannon entropy

Optik ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4206-4211 ◽  
Author(s):  
Xiao-Yong Liu ◽  
Rong-Li Li ◽  
Hong-Wei Zhao ◽  
Ting-Hai Cheng ◽  
Gao-Jian Cui ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Quality Assessment ◽  
Shannon Entropy ◽  
Digital Image ◽  
Image Correlation ◽  
Speckle Patterns

Quality assessment of laser speckle patterns for digital image correlation by a Multi-Factor Fusion Index

2020 ◽  
Vol 124 ◽  
pp. 105822 ◽  
Author(s):  
Jinlian Song ◽  
Jianhong Yang ◽  
Fujia Liu ◽  
Kefei Lu
Keyword(s):  
Digital Image Correlation ◽  
Quality Assessment ◽  
Digital Image ◽  
Laser Speckle ◽  
Image Correlation ◽  
Speckle Patterns ◽  
Fusion Index

scholarly journals Quality assessment of speckle patterns for digital image correlation

2006 ◽  
Vol 44 (11) ◽  
pp. 1132-1145 ◽  
Author(s):  
D. Lecompte ◽  
A. Smits ◽  
Sven Bossuyt ◽  
H. Sol ◽  
J. Vantomme ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Quality Assessment ◽  
Digital Image ◽  
Image Correlation ◽  
Speckle Patterns

scholarly journals Gradient Correlation Functions in Digital Image Correlation

2019 ◽  
Vol 9 (10) ◽  
pp. 2127 ◽  
Author(s):  
Mikael Sjödahl
Keyword(s):  
Correlation Function ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Correlation Functions ◽  
Laser Speckle ◽  
Image Correlation ◽  
Intensity Correlation ◽  
Intensity Correlation Function ◽  
Speckle Patterns ◽  
The Difference

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.

Strain Measurement by Digital Image Correlation: Influence of Two Types of Speckle Patterns Made from Rigid or Deformable Marks

Strain ◽  
2012 ◽  
Vol 48 (5) ◽  
pp. 357-365 ◽  
Author(s):  
Y. Barranger ◽  
P. Doumalin ◽  
J. C. Dupré ◽  
A. Germaneau
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Strain Measurement ◽  
Image Correlation ◽  
Speckle Patterns

Fabrication and optimization of micro-scale speckle patterns for digital image correlation

2015 ◽  
Vol 27 (1) ◽  
pp. 015203 ◽  
Author(s):  
Jianguo Zhu ◽  
Gaoshen Yan ◽  
Guanglong He ◽  
Lei Chen
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Image Correlation ◽  
Micro Scale ◽  
Speckle Patterns

Optimized digital speckle patterns for digital image correlation by consideration of both accuracy and efficiency

2018 ◽  
Vol 57 (4) ◽  
pp. 884 ◽  
Author(s):  
Zhenning Chen ◽  
Xinxing Shao ◽  
Xiangyang Xu ◽  
Xiaoyuan He
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Image Correlation ◽  
Speckle Patterns ◽  
Digital Speckle

Characterization of LIGA Microsystems Using Digital Image Correlation Technique and SEM Imaging

Aerospace ◽  
2005 ◽  
Author(s):  
Helena (Huiqing) Jin ◽  
Wei-Yang Lu ◽  
Jeff Chames ◽  
Nancy Yang
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Speckle Pattern ◽  
Image Correlation ◽  
Specimen Surface ◽  
Correlation Technique ◽  
Sem Images ◽  
Full Field ◽  
Speckle Patterns ◽  
Dic Technique

A new experimental technique was developed to characterize the mechanical properties of LIGA (an acronym from German words for lithography, electroplating, and molding) materials. An advanced imaging capability, scanning electron microscopy (SEM), with an integrated loading stage allows the acquisition of in situ microstructural images at the micro scale during loading. The load is measured directly from a load cell, and the displacement field is calculated from the SEM images based on the digital image correlation (DIC) technique. The DIC technique is a full-field deformation measurement technique which obtains displacement fields by comparing random speckle patterns on the specimen surface before and after deformation. The random speckle patterns are typically generated by applying a thin layer of material with high contrast to a specimen surface. Alternatively, DIC can also be applied using the microstructural features of a surface as texture patterns for correlation. DIC technique is ideally suited to characterize the deformation field of MEMS structures without the need to generate a random speckle pattern, which can be very challenging on the micro and nanoscale. In this paper, the technique is experimentally demonstrated on a LIGA specimen. The digital images showing LIGA surface features acquired during the loading can serve as random patterns for the DIC method. Therefore, full-field displacement and strain can be obtained directly on the specimen and the errors incurred by the testing system can be eliminated.

scholarly journals A Self-Adaptive Selection of Subset Size Method in Digital Image Correlation Based on Shannon Entropy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 184822-184833
Author(s):  
Xiao-Yong Liu ◽  
Xin-Zhou Qin ◽  
Rong-Li Li ◽  
Qi-Han Li ◽  
Song Gao ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Shannon Entropy ◽  
Digital Image ◽  
Image Correlation ◽  
Subset Size ◽  
Adaptive Selection ◽  
Selection Of ◽  
Self Adaptive
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