Name
Abstract | ||
|---|---|---|
In this paper, we present two types of the real-time water monitoring system using the image processing technology, the water level recognition and the surface velocity recognition. According to the bridge failure investigation, floods in the river often pose potential risk to bridges, and scouring could undermine the pier foundation and cause the structures to collapse. It is very important to develop monitoring techniques for bridge safety in the field. In this study, we installed two high-resolution cameras on the in-situ bridge site to get the real-time water level and surface velocity image. For the water level recognition, we use the image processing techniques of the image binarization, character recognition, and water line detection. For the surface velocity recognition, the proposed system apply the PIV(Particle Image Velocimetry, PIV) method to obtain the recognition of the water surface velocity by the cross correlation analysis. Finally, the proposed systems are used to record and measure the variations of the water level and surface velocity for a period of three days. The good results show that the proposed systems have potential to provide real-time information of water level and surface velocity during flood periods. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ISM.2013.49 | ISM |
Keywords | Field | DocType |
surface velocity recognition,water line detection,surface velocity,real-time water level,water surface velocity,water level recognition,image recognition,character recognition,water level,proposed system,real-time water monitoring system,flow measurement,hydraulic systems,fracture | Computer vision,Object detection,Particle image velocimetry,Hydraulic machinery,Computer science,Flow measurement,Pier,Image processing,Artificial intelligence,Condition monitoring,Water level | Conference |
Citations | PageRank | References |
2 | 0.72 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Franco Lin | 1 | 4 | 2.16 |
| Wen-Yi Chang | 2 | 12 | 3.34 |
| Lung-Cheng Lee | 3 | 2 | 1.39 |
| Hung-Ta Hsiao | 4 | 2 | 0.72 |
| Whey-Fone Tsai | 5 | 4 | 3.85 |
| Jihn-Sung Lai | 6 | 10 | 1.22 |