Automated and accurate initialization of digital image correlation for large deformation measurement

Yihao Zhou; Jubing Chen; Bing Pan

doi:10.1117/12.2017687

22 June 2013 Automated and accurate initialization of digital image correlation for large deformation measurement

Yihao Zhou, Jubing Chen, Bing Pan

Proceedings Volume 8769, International Conference on Optics in Precision Engineering and Nanotechnology (icOPEN2013); 87690P (2013) https://doi.org/10.1117/12.2017687
Event: International Conference on Optics in Precision Engineering and Nanotechnology (icOPEN2013), 2013, Singapore, Singapore

Abstract

Digital image correlation matches the corresponding locations in the reference and deformed images by optimizing the correlation of the related intensities. Iterative algorithm is regarded as the most effective approach to solving the optimization, but it requires accurate initial guess of the deformation parameters to converge correctly and rapidly. This paper presents a fully automated method which provides accurate initialization for all points of interest in a deformed images and deals with large rotation and heterogeneous deformation. Image features are extracted and pre-matched in the reference and the deformed images. The deformation parameter of a sample point is initialized by the mapping function fitted to the matched features in the vicinity. Once the subsequent iterative optimization achieves a qualified correlation measure, the optimized parameter is used to initiate a parameter transfer. To account for potential deformation difference between successive points, propagation functions are used during the transfer, which are analytically derived to accurately relate the parameters of two points separated by a given distance. The parameter transfer is conducted by the quality of correlation optimization and continued till all the points have been analyzed. Results on both simulated deformations and real-world experiments demonstrate that image features can be reliably matched and automatically generate qualified seed points even in the presence of complex transformation. Parameter transfer using propagation function enables rapid and correct convergence of the nonlinear iterative optimization, allows more flexible choice on the interval between adjacent sample points, and meanwhile handles the heterogeneity of the deformation field.

Citation Download Citation

Yihao Zhou, Jubing Chen, and Bing Pan "Automated and accurate initialization of digital image correlation for large deformation measurement", Proc. SPIE 8769, International Conference on Optics in Precision Engineering and Nanotechnology (icOPEN2013), 87690P (22 June 2013); https://doi.org/10.1117/12.2017687

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
12 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Digital image correlation

Correlation function

Speckle pattern

Statistical analysis

Image registration

Optimization (mathematics)

Speckle

Show All Keywords

Keywords/Phrases

Search In:

Publication Years