Systematic errors in digital image correlation caused by intensity interpolation

ABSTRACT: Recently, digital image correlation as a tool for surface deformation measurements has found widespread use and acceptance in the field of experimental mechanics. The method is known to reconstruct displacements with subpixel accuracy that depends on various factors such as image quality, noise, and the correlation algorithm chosen. However, the systematic errors of the method have not been studied in detail. We address the systematic errors of the iterative spatial domain crosscorrelation algorithm caused by gray-value interpolation. We investigate the position-dependent bias in a numerical study and show that it can lead to apparent strains of the order of 40% of the actual strain level. Furthermore, we present methods to reduce this bias to acceptable levels.

Systematic errors for a simulated uniaxial strain test for different interpolation functions: left, continuous gray-value distribution; right, bimodal distribution
Full Paper