Abstract:
Thisthesis proposed aThree Dimensional (3D) image acquiring technique with improved accuracy
3D model ofsmall high precision machine parts (stud mounted device) and presents to recreate a
a detailed Literature Review (LR) on 3D imaging techniques. 3D imaging has been used and
applied in several fields, such as computer vision, machine vision, medical science, optics and
robotics etc. The research in 3D applications development is progressing swiftly and industry is
making the most out ofit. To obtain 3D data and depth information, there different techniques that
urrently being used for different applications. These 3D acquisition techniques are mainly
is one that is the most
also be named as
are c
classified into different categories. Amongst them, stereo vision technique
well-known and used extensively in research and development. It can
triangulation technique. Additionally, Three-Dimensional Digital Image Correlation (3D-DIC),
Non-Rigid Structure from Motion (NRSFM), convex relaxation, structured light and coded
structured light techniques contributed a lot in the research. Nonetheless, the research community
of the fact that still much remains to be done. This thesis considered important is well aware
from the literature review and identified best suitable method to reconstruct dense 3D findings
shape of an object. The experiment performed using Structure from Motion (SFM) algorithm
combined with Clustering based Multiview Stereo algorithm and final shape retrieved using
screened poisson surface reconstruction technique. This method is adapted from previously
proposed method by Gupta et al. in [1], but the method was proposed to monitor land-sliding in
MATLAB for reading the sequence of 3D high resolution. The software used in this study
images and running SFM algorithm on the input images, Visual SFM is used for applying CMVS
algorithm on the point cloud produced by SFM and lastly Meshlab takes the CMVS output file
and reconstruct the surface ofthe object and produces a fine and accurate 3D model. The results
are
ofthe proposed method have been evaluated by calculating Mean Absolute Error and percentage
error between the observed and calculated values. The results show that the proposed technique
achieves better accuracy with reduce cost and computational time under particular conditions.
