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Multi-resolution Information Mining and a Computer Vision Approach to Pavement Condition Distress Analysis. Final Report
| 题名： | Multi-resolution Information Mining and a Computer Vision Approach to Pavement Condition Distress Analysis. Final Report |
| 作者： | Adu-Gyamfi, Y. O.; Attoh-Okine, N. |
| 关键词： | Pavements##Highway maintenance##Monitoring##Computer vision##Data acquisition##Data mining##Decision making##Geographical information systems##Highway design##Image processing##Preservation##Rehabilitation##Surveys##Pavement condition distress analysis## |
| 摘要： | Pavement Condition surveys are carried out periodically to gather information on pavement distresses that will guide decision-making for maintenance and preservation. Traditional methods involve manual pavement inspections which are time-consuming and subjective. In recent times, there has been a move towards automated methods of pavement condition assessment. The automated methods which comprise of acquiring pavement data with cameras and analyzing the images have several shortcomings, especially in the area of image analysis. A major problem is that most of the image processing algorithms are based on assumptions that may not work well under certain conditions. Therefore, there is a need for adaptive image processing methods that are robust under varying conditions. This study focused on the use of multi-resolution information-mining techniques with a computer vision approach to analyze pavement conditions. A vision-system which seeks to fully-automate the pavement condition survey process is also developed. With a user-friendly interface and GIS integration, the vision system comprising of three main components; image acquisition, image retrieval and the output analysis and visualization component, this system will serve as the foundation for the future of fully-automated pavement distress surveys. |
| 总页数： | 153 |
| 报告类型： | 科技报告 |
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