Undergraduate Research

3D Full-field Deformation Measurement using Digital Image Correlation

University of Moratuwa, Sri Lanka Jan 2020 – Jul 2021 Supervisor: Prof. Chinthaka Mallikarachchi
Overview

This project developed a Digital Image Correlation (DIC) based algorithm capable of computing full-field displacement and strain from photographs taken by ordinary digital cameras. Unlike commercial DIC systems that typically require specialised hardware, the method was designed to work with widely available equipment, making it a practical, low-cost tool for laboratory-scale civil engineering experiments.

A GUI-driven standalone application was built in MATLAB, allowing users to load stereo image pairs and obtain full-field 3D displacement and strain maps without needing to interact with the underlying code. The system was validated through a series of physical tests, including rigid body motion tests, tensile and compression tests, and trial measurements of plastic shrinkage cracks in mortar.

Gallery
Stereo camera rig and laptop setup used for DIC image capture Specimen positioned under the loading frame for DIC testing
Speckle-patterned specimen used for digital image correlation Computed displacement and strain field results from the DIC algorithm
Details
Objective
Developing a Digital Image Correlation (DIC) based algorithm that can compute displacement and strain using photographs taken by digital cameras.
Application
Developed a GUI-driven standalone application using MATLAB.
Features
  • 3D full-field deformation measurement
  • Effective for lab-scale civil engineering experiments
  • Easy-to-handle application
Testing
Carried out rigid body motion tests, tensile and compression tests, and initial trial tests of plastic shrinkage cracks using mortar.
Publications

L. S. Sarma and C. Mallikarachchi, "3D Full-field Deformation Measurement using Stereo Vision," in 2022 Moratuwa Engineering Research Conference (MERCon), IEEE, pp. 1–6. [Link]

S. Nadarajah, L. S. Sarma, and C. Mallikarachchi, "Semi-Automated Crack Detection Using Computer Vision," in Proceedings of the Annual Sessions of the Society of Structural Engineers Sri Lanka, Colombo, Sri Lanka, Aug. 2020, pp. 38–43. [Link]

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