Feature-based template approach for optimizing digital image correlation on complex deformations

Sneha Prasad; David Kumar; Sumit Kalra; Arpit Khandelwal

doi:10.1117/12.3012491

9 May 2024 Feature-based template approach for optimizing digital image correlation on complex deformations

Sneha Prasad, David Kumar, Sumit Kalra, Arpit Khandelwal

Proceedings Volume 12951, Health Monitoring of Structural and Biological Systems XVIII; 129512B (2024) https://doi.org/10.1117/12.3012491
Event: SPIE Smart Structures + Nondestructive Evaluation, 2024, Long Beach, California, United States

Abstract

The initialization method in Digital Image Correlation (DIC) is essential for optimizing the correlation criteria and accurately computing the deformations of a material under load. At present, feature-based initialization techniques are widely explored for predicting the deformations of various complex circumstances, such as large deformations for soft materials, non-continuous deformations in heterogeneous materials, etc. However, due to the non-uniform distribution of the detected features, the initialization process goes through biased prediction. This bias occurs due to the sparsity of features in different regions of the sample, which can lead to inaccuracy in identifying the shape of deformation. This study addresses the issue of feature distribution and develops a feature-based template approach for providing initialization points for each subset on a finer scale. The features (interest points) are determined using KAZE feature detector and descriptor algorithm in nonlinear scale space due to its ability to determine consistent, repeatable, distinct features invariant to scale and rotation. The proposed algorithm uses bi-cubic b-spline interpolation to identify the strongest interest point at the subpixel level for each subset (of the input sample images), which works as an initial value for estimating the deformation. Further, a threshold-based incremental reference approach is developed for measuring large deformations and avoiding the cumulative errors associated with the commonly used incremental reference strategy, which is compute-intensive because of the comparison between every previous image and the subsequent images.

Conference Presentation

Citation Download Citation

Sneha Prasad, David Kumar, Sumit Kalra, and Arpit Khandelwal "Feature-based template approach for optimizing digital image correlation on complex deformations", Proc. SPIE 12951, Health Monitoring of Structural and Biological Systems XVIII, 129512B (9 May 2024); https://doi.org/10.1117/12.3012491

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