  Internal properties of a sample can be observed by medical imaging tools,
such as ultrasound devices, magnetic resonance imaging (MRI) and optical
coherence tomography (OCT) which are based on relying on changes in material
density or chemical composition [1-21]. As a preliminary investigation, the
feasibility to detect interior defects inferred from the discrepancy in
elasticity modulus distribution of a three-dimensional heterogeneous sample
using only surface full-field measurements and finite element model updating as
an inverse optimization algorithm without any assumption about local
homogeneities and also the elasticity modulus distribution is investigated.
Recently, the authors took advantages of the digital image correlation
technique as a full field measurement in constitutive property identification
of a full-scale steel component [22-27]. To the extension of previous works, in
this brief technical note, the new idea intended at recovering unseen
volumetric defect distributions within the interior of three-dimensional
heterogeneous space of the structural component using 3D-Digital Image
Correlation for structural identification [28-57]. As a proof of concept, the
results of this paper illustrate the potential to identify invisible internal
defect by the proposed computer vision technique establishes the potential for
new opportunities to characterize internal heterogeneous materials for their
mechanical property distribution and condition state.
