The monitoring of possible damages on industrial plants from aerial images represents a challenging task. In this work, we present a methodology to monitor the changes due to corrosion damages on industrial plants by using Unmanned Aerial Vehicle (UAV) images. First, a couple of images acquired at two different times is considered and aligned to each other through a geometric transformation. Then, the possible changes are highlighted in both images by exploiting a simple automatic thresholding technique based on the assumption that damages have usually different aspects with respect to the surrounding structures. At the end, the images are compared to obtain an estimation of the damage growth. The methodology has been tested on extremely high resolution images obtained with different acquisition conditions. The achieved results demonstrate the precision of the method and suggest the possible use of such a technique in practical applications.

Monitoring Structural Damages in Big Industrial Plants with UAV Images

Moranduzzo, Thomas;Melgani, Farid
2014-01-01

Abstract

The monitoring of possible damages on industrial plants from aerial images represents a challenging task. In this work, we present a methodology to monitor the changes due to corrosion damages on industrial plants by using Unmanned Aerial Vehicle (UAV) images. First, a couple of images acquired at two different times is considered and aligned to each other through a geometric transformation. Then, the possible changes are highlighted in both images by exploiting a simple automatic thresholding technique based on the assumption that damages have usually different aspects with respect to the surrounding structures. At the end, the images are compared to obtain an estimation of the damage growth. The methodology has been tested on extremely high resolution images obtained with different acquisition conditions. The achieved results demonstrate the precision of the method and suggest the possible use of such a technique in practical applications.
2014
IEEE-International Geoscience and Remote Sensing Symposium IGARSS-2014
USA, New York
IEEE
9781479957750
Moranduzzo, Thomas; Melgani, Farid
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/101471
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