DICLab2D: An open-source digital image correlation algorithm for Julia language

SoftwareX 2026 Open access

Read full text
Authors: Dennis Quaresma Pureza, José Luis Vital de Brito, Guilherme Santana Alencar, Luís Augusto Conte Mendes Veloso
DOI: 10.1016/j.softx.2026.102532
Cited by: 1
References: 13

Abstract

This work presents DICLab2D, an open-source digital image correlation (DIC) algorithm developed in the Julia programming language. DICLab2D is a local subset-based 2D DIC code that employs both the inverse compositional Gauss-Newton (IC-GN) and the backward subtractive Gauss-Newton (BS-GN) methods. The algorithm is equipped with shape functions up to the fourth order, reliability-guided displacement tracking, and a dual analysis mode - area and line probes. Standardized tests from the DIC challenge were used to evaluate algorithm performance. The results show that DICLab2D achieves performance equivalent or exceeding that of existing commercial and open-source DIC codes.

Fields of Study & Subjects

Optical measurement and interference techniques Advanced Vision and Imaging Advanced Image Processing Techniques

Publication details

Journal / source
SoftwareX
Publisher
Elsevier BV
Volume
33
Pages
102532–102532
Publication date
24 January 2026
Language
EN