Earthquake damage detection using watershed segmentation and intensity-gradient orientation approaches

Sümer, Emre
Earthquake is one of the most destructive natural disasters on earth. Rapid and reliable post-quake damage assessment has an important role to reduce the drastic effects of an earthquake by setting the responsible agencies in motion. In this study, the collapsed buildings due to earthquake were detected from post-event aerial images. Two approaches were proposed to detect the collapsed buildings. These approaches were implemented in a selected urban area of Golcuk. The first approach was based on the analysis of shadow casting edges. First, the shadow casting edges of the buildings were identified and a buffer zone was generated for each building polygon along these edges. Then, the shadow regions were detected using the watershed segmentation algorithm. This was followed by measuring the agreement between the shadow producing edges of the buildings and their corresponding shadows. Of the 284 buildings analyzed, 229 were successfully labeled as collapsed or un-collapsed providing an overall accuracy of 80,63%.In the second approach, a two-branch method based on building light intensities and the gradient orientation was used. In the first branch, an intensity threshold was determined and applied to building image patches. Then, a pixel ratio was computed to categorize the buildings. In the second branch, a series of processings were carried out including the smoothing of the building image patches and the determination of the magnitude and the orientation of the gradient. Then, an optimum angle threshold was determined to label the buildings. The final decision about the condition of a building was made by integrating the two branches. Of the 284 buildings analyzed, 254 were correctly labeled providing an overall accuracy of 89,44%. The same assessments were repeated after generating a one-pixel wide buffer zone around the building polygons and an overall accuracy of


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Citation Formats
E. Sümer, “Earthquake damage detection using watershed segmentation and intensity-gradient orientation approaches,” M.S. - Master of Science, Middle East Technical University, 2004.