LAUSR

Digital Image Correlation (DIC) is a length scale independent surface pattern matching and tracking algorithm capable of providing full field deformation measurements. The confident registration of this pattern within the imaging system becomes key to the derived results. Practically, conventional speckling methods use non-reliable, non-repeatable patterning methodologies including spray paints and air brushing leading to increased systematic and random errors based on the user’s experience. A methodology to develop a speckle pattern tailored to the imaging and experimental conditions of the given system is developed in this paper. In this context, a novel bio-inspired speckle pattern development technique is introduced, leveraging spatial imaging parameters in addition to frequency characteristics of speckle patterns, enhancing the results obtained through DIC. This novel technique leverages gradient parameters in the frequency spectrum obtained from patterns fabricated using a bio-templating manufacturing technique. The analysis presented shows that optimized gradient features alongside tailored spatial characteristics reduce errors while increasing the usefulness of DIC results across the entire region of interest. With this new approach, gradient information is derived from the bio-templated pattern, extracted, optimized and then convolved with spatial properties of a numerically generated 2D point clouds which can then be transferred onto actual specimens. Numerical error analysis shows that the optimized patterns result in significant reduction in root mean square error compared to conventional speckling methods. Physical experiments show the scalability of this optimized pattern to allow for varying working distances while consistently maintaining a lower error threshold compared to conventional speckling techniques.