| Imagery Enhancement and Interpretation for Remote Visual Inspection of Aging Civil Infrastructure |
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| 作者单位： | Department of Civil and Environmental Engineering，Carnegie Mellon University |
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| 基金项目： | the Innovative Management & Technology Services-National Aeronautics and Space Administration (IMTS-NASA) grant, and the Pennsylvania Infrastructure Technology Alliance. |
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| 摘 要： | In this paper, we describe an image enhancement and interpretation methodology to enhance and recognize surface defects and critical patterns from remote imagery of sewer pipeline inspection. The objective is to provide inspectors and professionals with better tools to allow them to examine the imagery for condition assessment. We present initial results of a collaboration with a robotic company through a case study on computer-assisted processing and interpretation of sewer pipeline inspection imagery. In the mean time, the described enhancement and interpretation methodology can also be applied to sewer pipeline condition assessment in an offline mode, where this methodology can support professionals’ examination of acquired sewer condition imagery.
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| 关 键 词： | remote visual inspection infrastructure assessment image processing and analysis defects region of interest detection classification |
Imagery Enhancement and Interpretation for Remote Visual Inspection of Aging Civil Infrastructure |
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| Authors: | Wei Guo Lucio Soibelman James H Garrett |
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| Institution: | Department of Civil and Environmental Engineering, Carnegie Mellon University |
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| Abstract: | In this paper, we describe an image enhancement and interpretation methodology to enhance and recognize surface defects and critical patterns from remote imagery of sewer pipeline inspection. The objective is to provide inspectors and professionals with better tools to allow them to examine the imagery for condition assessment. We present initial results of a collaboration with a robotic company through a case study on computer-assisted processing and interpretation of sewer pipeline inspection imagery. In the mean time, the described enhancement and interpretation methodology can also be applied to sewer pipeline condition assessment in an offline mode, where this methodology can support professionals' examination of acquired sewer condition imagery. |
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| Keywords: | remote visual inspection infrastructure assessment image processing and analysis defects region of interest detection classification |
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