Pydic: 2D-DIC Code Accuracy Evaluation for Strain Field Measurements

Authors:
Publisher website
Google Scholar
Abstract
Modern personal computer machines with high-capacity processors allow the application of advanced techniques in the field of testing and inspection for civil and mechanical engineering. Digital Image Correlation is currently one of the most cost-effective and user-friendly optical and noncontact techniques for strain field measurements. Pydic is a free and open source Python code for local 2D Digital Image Correlation. It was developed by Damien André, SPCTS/ENSIL-ENSCI, Limoges, France. Pydic is based on OpenCV, a well-known open-source computer vision and machine learning library. In this work, the Pydic code was validated for strain field measurements using a set of speckled images provided by the SEM DIC challenge. The same set of speckled images was used to compute the strain field with GOM correlate software. An accuracy assessment was made by comparing the results of Pydic code and GOM correlate software; also, the results published in the DIC challenge report were considered in the comparison. The results show an acceptable agreement by visual comparison and the computed strain field range. The weaknesses of Pydic code were highlighted, and future work for code improvement was discussed.