Conference contribution
(Conference Contribution)


Automatic detection and analysis of photovoltaic modules in aerial infrared imagery


Publication Details
Author(s): Dotenco S, Dalsass M, Winkler L, Wurzner T, Brabec C, Maier A, Gallwitz F
Publisher: Institute of Electrical and Electronics Engineers Inc.
Publication year: 2016
ISBN: 9781509006410
Event: IEEE Winter Conference on Applications of Computer Vision, WACV 2016
Language: English

Abstract

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.



How to cite
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. Institute of Electrical and Electronics Engineers Inc..

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, WACV 2016 Institute of Electrical and Electronics Engineers Inc., 2016.

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