United States Department of Transportation
i
Transportation informatics : an image analysis system for managing transportation facilities – phase II.
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2012-02-01
[PDF-1.83 MB]
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Abstract:One of the most important tasks in maintaining transportation facilities such as highways
and streets is the evaluation of the existing condition. Visual evaluation by human
inspectors is subjective in nature, therefore has issues of consistency and the speed and
frequency of evaluation is limited due to the manual process. Automated evaluation
using modern digital image processing and pattern recognition techniques can increase
the efficiency and accuracy and decrease the costs of condition evaluation. Several
automated condition evaluation systems have been developed, but these systems
commonly require special devices such as strobe light, laser beams, etc, which increase
the cost and limit the system to certain applications. In this study, a low cost automatic
pavement distress evaluation approach is presented. This method can provide real-time
pavement distress detection as well as evaluation results based on color images captured
from a camera installed on a survey vehicle. The entire process consists of two main
parts: pavement surface extraction followed by pavement distress detection and
classification. In the first part, a novel color segmentation method based on a feed
forward neural network is employed to separate the road surface from the background.
In the second part, a segmentation technique based on probabilistic relaxation is used to
separate distress areas from the road surface. The geometrical parameters obtained from
the detected distresses are then fed to a neural network based pavement distress classifier
in which the defects are classified into different types. Simulation results are given to
show that the scheme presented in this report is both effective and reliable on a variety of
pavement images.
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