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Road Distress Analysis using 2D and 3D Information

Bao, Guanqun
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1289874675

Abstract Details

2010, Master of Science in Electrical Engineering, University of Toledo, Electrical Engineering.
During the last few decades, many efforts have been made to produce automatic inspection systems to meet the specific requirements in assessing distress on the road surfaces using video cameras and image processing algorithms. However, due to the noisy pavement surfaces, limited success was accomplished. One major issue with pure video based systems is their inability to discriminate dark areas not caused by pavement distress such as tire marks, oil spills, shadows, and recent fillings. To overcome the limitation of the conventional imaging based methods, novel pavement inspection approaches based on both 2-dimensional (2D) and 3-dimensional (3D) information are proposed in this thesis. Techniques such as 2D feature extraction, morphological operations, artificial neural networks, and 3D model reconstruction are utilized successively within the research. The primary goal of this study is to integrate conventional image processing techniques with stereovision technology to provide a full dimensional visualization of the pavement surface. With segmentation results from the 2D images and depth information estimated by 3D reconstruction, the detailed topological structure of the road defects can be accurately obtained. Simulation results show the proposed system is effective and robust on a variety of pavement surfaces.
Ezzatollah Salari, PhD (Committee Chair)
Henry Ledgard, PhD (Committee Member)
Junghwan Kim, PhD (Committee Member)
108 p.
Electrical Engineering
pavement inspection; stereo vision; neural network; segmentation

Recommended Citations

Citations

  • Bao, G. (2010). Road Distress Analysis using 2D and 3D Information [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1289874675

    APA Style (7th edition)

  • Bao, Guanqun. Road Distress Analysis using 2D and 3D Information. 2010. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1289874675.

    MLA Style (8th edition)

  • Bao, Guanqun. "Road Distress Analysis using 2D and 3D Information." Master's thesis, University of Toledo, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1289874675

    Chicago Manual of Style (17th edition)

toledo1289874675
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© 2010, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.