Smartphone based scalable reverse engineering by digital image correlation

Amey Vidvans, Saurabh Basu

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

There is a need for scalable open source 3D reconstruction systems for reverse engineering. This is because most commercially available reconstruction systems are capital and resource intensive. To address this, a novel reconstruction technique is proposed. The technique involves digital image correlation based characterization of surface speeds followed by normalization with respect to angular speed during rigid body rotational motion of the specimen. Proof of concept of the same is demonstrated and validated using simulation and empirical characterization. Towards this, smart-phone imaging and inexpensive off the shelf components along with those fabricated additively using poly-lactic acid polymer with a standard 3D printer are used. Some sources of error in this reconstruction methodology are discussed. It is seen that high curvatures on the surface suppress accuracy of reconstruction. Reasons behind this are delineated in the nature of the correlation function. Theoretically achievable resolution during smart-phone based 3D reconstruction by digital image correlation is derived.

Original languageEnglish (US)
Pages (from-to)1339-1351
Number of pages13
JournalOptics and Lasers in Engineering
Volume102
DOIs
StatePublished - Mar 1 2018

Fingerprint

reverse engineering
Reverse engineering
Smartphones
3D printers
Lactic acid
Polymers
Imaging techniques
digital techniques
lactic acid
printers
rigid structures
shelves
resources
curvature
methodology
polymers
poly(lactic acid)

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Cite this

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Smartphone based scalable reverse engineering by digital image correlation. / Vidvans, Amey; Basu, Saurabh.

In: Optics and Lasers in Engineering, Vol. 102, 01.03.2018, p. 1339-1351.

Research output: Contribution to journalArticle

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