OpenLSA: An open-source toolbox for computing full-field displacements from images of periodic patterns

Abstract

In the experimental mechanics community, full-field measurement techniques have gained popularity over the last few decades, revolutionizing traditional testing procedures for materials and structures. While Digital Image Correlation (DIC) remains the most widely used method, its reliance on randomly patterned surfaces limits its metrological performance, and the iterative calculations required for retrieving displacement and strain fields can be computationally expensive. In recent years, there has been a proposal to use optimal checkerboard patterns instead. Images of such periodic patterns can be processed using a method called Localized Spectrum Analysis (LSA). LSA proposes processing these images in the frequency domain using spectral techniques, which reduces computational costs. This paper presents an open-source LSA software written in Python and illustrates two application cases in experimental mechanics.

Keywords

• Experimental mechanics
• Full-field measurements
• Digital image correlation
• Localized spectrum analysis