Issue 77

T. Hachimi et alii, Fracture and Structural Integrity, 77 (2026) 173-206; DOI: 10.3221/IGF-ESIS.77.11

Language / Platform

Software

2D/3D

Approach

Key Characteristic Intuitive GUI; multi platform;

Link / Source

DICe

2D/3D

Local / Global

C++

GitHub

FEM-based DIC; research oriented Robust ROI updates for large deformation Lightweight; easy to use FEM global DIC; strong research usage Validated vs commercial DIC High-performance; large datasets GUI for specific calibration parameters Modern, high-performance DIC Low-cost experimental setup End-to-end DisplacementNet/StrainNet Neural Operator for scale generalization Modern Python DIC; GUI + API; Benchmarked against DIC Challenge 2.0 High-order shape functions (up to 4th order) Stereo DIC; well documented

dolfin_dic

2D/3D

Global

Python

Bitbucket

Website

Ncorr

2D

Local

MATLAB

Pydic

2D

Local

Python

GitLab

Pyxel

2D

Global

Python

GitHub

Py2DIC

2D

Local

Python

GitHub

YaDICs

2D/3D

Local / Global

C++

Website

iCorrVision

2D

Local

Python

GitHub

OpenCorr

2D/3D

Local / Global

C++

OpenCorr.org

MultiDIC

3D

Global

MATLAB

Stereo DIC; calibration tools MIT Media Lab

(Unspecified, Global)

DuoDIC

3D

MATLAB

JOSS Publication

Python + Raspberry Pi Python / DL frameworks

GitHub / ScienceDirect

RealPi2dDIC 2D

Local

Global (Deep Learning)

Deep DIC

2D

arXiv

DICNO

2D/3D

Operator

Python

DICNO

SUN-DIC

SUN-DIC

2D

Local

Python

DICLab2D

2D

Local

Julia

DICLab2D

Table 2: Features of Select DIC Open-Source Software.

Standardization and metrological reporting For the industrial application of DIC, it is necessary to follow established protocols for quantifying uncertainty and preparing reports. Through the DIC Challenge 2.0, Reu et al. [91] created the Metrological Efficiency Indicator (MEI), which quantitatively defines the tradeoff between noise and resolution. To aid in the establishment of uncertainty propagation models for VSGs, Beck [11] and Grédiac et al. [42] summarized the components of an uncertainty propagation model and also provided a means for calculating the sensitivity of the respective hardware to predict system performance of DICs over time. For required operational compliance with ANSI (2026) and ISO 10012:2026 measurement management standards, these requirements have also been established by Jones et al. [51] and outlined in the NCAL/NIST iDICs Good Practices Guide through minimum calibration and reporting requirements. Ahmad et al. [3] validated these standards during the Stereo-DIC Challenge 1.0 by successfully demonstrating that the stated protocols for DIC enable robust evaluation of non planar AM geometries. These metrological standards serve as the foundation for transitioning DIC from the realm of academic research into that of certified industrial use, which is summarized in Table 3.

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