Title:
Tracking and detection of cracks using minimal path techniques
Tracking and detection of cracks using minimal path techniques
Author(s)
Kaul, Vivek
Advisor(s)
Yezzi, Anthony
Tsai, Yi-Chang James
Tsai, Yi-Chang James
Editor(s)
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Abstract
The research in the thesis investigates the use of minimal path techniques to track and
detect cracks, modeled as curves, in critical infrastructure like pavements and bridges. We
developed a novel minimal path algorithm to detect curves with complex topology that may
have both closed cycles and open sections using an arbitrary point on the curve as the sole
input. Specically, we applied the novel algorithm to three problems: semi-automatic crack
detection, detection of continuous cracks for crack sealing applications and detection of crack
growth in structures like bridges. The current state of the art minimal path techniques only
work with prior knowledge of either both terminal points or one terminal point plus total
length of the curve. For curves with multiple branches, all terminal points need to be known.
Therefore, we developed a new algorithm that detects curves and relaxes the necessary user
input to one arbitrary point on the curve. The document presents the systematic development
of this algorithm in three stages. First, an algorithm that can detect open curves with
branches was formulated. Then this algorithm was modied to detect curves that also have
closed cycles. Finally, a robust curve detection algorithm was devised that can increase the
accuracy of curve detection. The algorithm was applied to crack images and the results of
crack detection were validated against the ground truth. In addition, the algorithm was also
used to detect features like catheter tube and optical nerves in medical images. The results
demonstrate that the algorithm is able to accurately detect objects that can be modeled as
open curves.
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Date Issued
2010-08-27
Extent
Resource Type
Text
Resource Subtype
Dissertation