Inundated Areas Extraction Based on Raindrop Photometric Model (RPM) in Surveillance Video

Abstract

Monitoring and assessing urban flood disasters is the key to reducing the damage of this hazard. The urban surveillance video, with the advantages of flexibility and low cost, has been used as an effective real-time data source to monitor urban flooding. The paper presents an inundated area extraction method based on raindrop photometric model. The proposed method operates on the video and divides the task into two steps: (1) extracting water surface, followed by (2) refining inundated areas. At the first step in the process, the water covered areas are extracted from the variation of video in time series. This procedure was an improved version of the raindrop photometric model. Constrained information, especially road ranges, was obtained from video background image which has eliminated interference factors. Then inundated areas can be refined with the constraint information. Experiments performed on different locations show that the proposed method can provide more reliable results than the traditional method based on spectral features.