Indiana University-Purdue University Indianapolis (IUPUI) / Close range, image based photogrammetry and LIDAR laser scanning technique
are commonly utilized methodologies to snap real objects.3D models of already existing
model or parts can be reconstructed by laser scanning and photogrammetry.
These 3D models can be useful in applications like quality inspection, reverse engineering.
With these techniques, they have their merits and limitations. Though laser scanners
have higher accuracy, they require higher initial investment. Close-range photogrammetry
is known for its simplicity, versatility and e ective detection of complex
surfaces and 3D measurement of parts. But photogrammetry techniques can be initiated
with comparatively much lower initial cost with acceptable accuracy.
Currently, many industries are using photogrammetry for reverse engineering,
quality inspection purposes. But, for photogrammetric object reconstruction, they
are using di erent softwares. Industrial researchers are using commercial/open source
codes for reconstruction and another stand-alone software for reverse engineering and
mesh deviation analysis.
So the problem statement here for this thesis is to integrate Photogrammetry,
reverse engineering and deviation analysis to make one state-of-the-art
work
ow.
xx
The objectives of this thesis are as follows:
1. Comparative study between available source codes and identify suitable and
stable code for integration; understand the photogrammetry methodology of
that particular code.
2. To create a taskpane add-in using API for Integration of selected photogrammetry
methodology and facilitate methodology with parameters.
3. To demonstrate the photogrammetric work
ow followed by a reverse engineering
case studies to showcase the potential of integration.
4. Parametric study for number of images vs accuracy
5. Comparison of Scan results, photogrammetry results with actual CAD data
Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/19992 |
Date | 08 1900 |
Creators | Potabatti, Nikhil S. |
Contributors | El-Mounayri, Hazim, Chen, Jie, Anwar, Sohel |
Source Sets | Indiana University-Purdue University Indianapolis |
Language | English |
Detected Language | English |
Type | Thesis |
Rights | CC0 1.0 Universal, http://creativecommons.org/publicdomain/zero/1.0/ |
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