Transportation informatics : an image analysis system for managing transportation facilities – phase II.
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Transportation informatics : an image analysis system for managing transportation facilities – phase II.

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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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