Optimized Patterns for Digital Image Correlation
This work presents theoretical background on a novel class of strain sensor patterns. A combination of morphological image processing and Fourier analysis is used to characterize gray-scale images, according to specific criteria, and to synthesize patterns that score particularly well on these criteria. The criteria are designed to evaluate, with a single digital image of a pattern, the suitability of a series of images of that pattern for full-field displacement measurements by digital image correlation (DIC). Firstly, morphological operations are used to flag large featureless areas and to remove from consideration features too small to be resolved. Secondly, the autocorrelation peak sharpness radius en the autocorrelation margin are introduced to quantify the sensitivity and robustness, respectively, expected when using these images in DIC algorithms. For simple patterns these characteristics vary in direct proportion to each other, but it is shown how to synthesize a range of patterns with wide autocorrelation margins even though the autocorrelation peaks are sharp. Such patterns are exceptionally well-suited for DIC measurements.
This research is funded by the ISMO project of the Multidisciplinary Institute for Digitalisation and Energy (MIDE) of Aalto University and by the Academy of Finland. Experimental verification of the performance of DIC measurements using patterns such as those described here has been carried out in collaboration with Bachir Belkassem at the Vrije Universiteit Brussel.
- 1.Sutton MA, Orteu JJ, Schreier HW (2009) Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications. Springer, New YorkGoogle Scholar
- 5.Pan B, Qian K, Xie H, Asundi A (2008) On errors of digital image correlation due to speckle patterns. In: He X, Xie H, Kang Y (eds) ICEM 2008: international conference on experimental mechanics 2008, vols 7375, 73754Z. SPIE, BellinghamGoogle Scholar
- 6.Collette SA et al (2004) Development of patterns for nanoscale strain measurements: I. fabrication of imprinted Au webs for polymeric materials. Nanotechnology 15:1812Google Scholar