Dotenco S, Dalsaß M, Winkler L, Wurzner T, Brabec C, Maier A, Gallwitz F (2016)
Publication Language: English
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2016
Publisher: IEEE
Article Number: 7477658
Event location: Lake Placid, NY
ISBN: 9781509006410
DOI: 10.1109/WACV.2016.7477658
Drone-based aerial thermography has become a convenient quality assessment tool for the precise localization of defective modules and cells in large photovoltaic-power plants. However, manual evaluation of aerial infrared recordings can be extremely time-consuming. Therefore, we propose an approach for automatic detection and analysis of photovoltaic modules in aerial infrared images. Significant temperature abnormalities such as hot spots and hot areas can be identified using our processing pipeline. To identify such defects, we first detect the individual modules in infrared images, and then use statistical tests to detect the defective modules. A quantitative evaluation of the detection and analysis pipeline on real-world, infrared recordings shows the applicability of our approach.
APA:
Dotenco, S., Dalsaß, M., Winkler, L., Wurzner, T., Brabec, C., Maier, A., & Gallwitz, F. (2016). Automatic Detection and Analysis of Photovoltaic Modules in Aerial Infrared Imagery. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision. Lake Placid, NY, US: IEEE.
MLA:
Dotenco, Sergiu, et al. "Automatic Detection and Analysis of Photovoltaic Modules in Aerial Infrared Imagery." Proceedings of the IEEE Winter Conference on Applications of Computer Vision, Lake Placid, NY IEEE, 2016.
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