Digital Image Correlation Engine

National Laboratory: 
Sandia National Laboratories
Characterization Class: 
Mechanical Behavior of Materials
Processing/Manufacturing Class: 
Shaping and forming

Digital image correlation (DIC) is a non-contact means of measuring motion and full-field displacements using only digital images of the object studied. DIC also involves computing strains as a secondary step once the displacement field is acquired. The Digital Image Correlation Engine, or DICe, currently is being used to calibrate material models, quality test NW components using high-speed video, and investigate extreme loading on NW components.

Capability Bounds: 

DICe is written for extreme scales in terms of processing high-speed video, streaming results in real time, and highly resolved computational meshes.

Unique Aspects: 

The subsets used for analysis in DICe can be of arbitrary shape (conforming to the object of interest). DICe also has a simplex-based optimization scheme that does not require painting patterns on the object. Presently, DICe is developing a well-posed DIC formulation that addresses numerical stability issues present in most DIC codes.


DICe is open source; builds and runs on Mac, Linux, and Windows; and can be compiled from source or installed via a package installer.

Single Point of Contact: 

Name: Dan Turner
Phone: 505-845-7446

  1. RB Lehoucq, PL Reu, and DZ Turner, A Novel Class of Strain Measures for Digital Image Correlation, Strain 51(4) 265-275, 2015
  2. DZ Turner, B Van Bloemen Waanders, and ML Parks, Inverse Problems in Heterogeneous and Fractured Media Using Peridynamics, Journal of Mechanics of Materials and Structures, Accepted, 2015
  3. PL Reu, E Johnson, D VanGoethem and S Walkington, Stereo Tracking for Shock Experiments – Processing and Uncertainty Quantification, SAND Report 2015.
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