Smart Structures and Systems

  • 제15권6호
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  • Pages.1583-1600
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  • 2015
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Smart monitoring system with multi-criteria decision using a feature based computer vision technique

  • Lin, Chih-Wei (Department of Computer Science and Information Engineering, National Taiwan University) ;
  • Hsu, Wen-Ko (Research Center for Hazard Mitigation and Prevention, National Central University) ;
  • Chiou, Dung-Jiang (Research Center for Hazard Mitigation and Prevention, National Central University) ;
  • Chen, Cheng-Wu (Department of Maritime Information and Technology, National Kaohsiung Marine University) ;
  • Chiang, Wei-Ling (Department of Civil Engineering, National Central University)
  • 투고 : 2014.03.18
  • 심사 : 2014.07.07
  • 발행 : 2015.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The "background module" and "monitoring module" procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.

키워드

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