Correcting for Perspective Distortion in Electroluminescence Images of Photovoltaic Panels

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Abstract

With the significant growth in the number of photovoltaic (PV) installations and their size, regular PV system inspection has become a challenge. Aerial drone imaging, based on visual, thermographic, and more recently luminescence, can be viable solutions for PV inspection. However, to achieve effective detection and quantification of failure based on images acquired form Unmanned Aerial Vehicle, there is need for image quality enhancement and correction of distortions, inherent to the drone measurement process. In this work we propose methods to automatically correct the perspective distortion in electroluminescent (EL) images of PV panels. We identified two main cases of perspective distortion: when the imaging plane is parallel to the panel plane or not, and propose methods to correct both. For both cases, theproposed method yields good results, as assessed by visual evaluation.
Original languageEnglish
Title of host publicationProceedings of 7th World Conference on Photovoltaic Energy Conversion
Number of pages5
PublisherIEEE
Publication date2018
ISBN (Print)9781538685297
DOIs
Publication statusPublished - 2018
Event7th World Conference on Photovoltaic Energy Conversion - Hilton Waikoloa Village Resort, Waikoloa, United States
Duration: 10 Jun 201815 Jun 2018
Conference number: WCPEC-7

Conference

Conference7th World Conference on Photovoltaic Energy Conversion
NumberWCPEC-7
LocationHilton Waikoloa Village Resort
CountryUnited States
CityWaikoloa
Period10/06/201815/06/2018

Cite this

@inproceedings{da6c754b77384defa9c25dc9fcda4e44,
title = "Correcting for Perspective Distortion in Electroluminescence Images of Photovoltaic Panels",
abstract = "With the significant growth in the number of photovoltaic (PV) installations and their size, regular PV system inspection has become a challenge. Aerial drone imaging, based on visual, thermographic, and more recently luminescence, can be viable solutions for PV inspection. However, to achieve effective detection and quantification of failure based on images acquired form Unmanned Aerial Vehicle, there is need for image quality enhancement and correction of distortions, inherent to the drone measurement process. In this work we propose methods to automatically correct the perspective distortion in electroluminescent (EL) images of PV panels. We identified two main cases of perspective distortion: when the imaging plane is parallel to the panel plane or not, and propose methods to correct both. For both cases, theproposed method yields good results, as assessed by visual evaluation.",
author = "Claire Mantel and Sergiu Spataru and Harsh Parikh and Dezso Sera and Benatto, {Gisele Alves dos Reis} and Nicholas Riedel and Sune Thorsteinsson and Poulsen, {Peter Behrensdorff} and S{\o}ren Forchhammer",
year = "2018",
doi = "10.1109/PVSC.2018.8547724",
language = "English",
isbn = "9781538685297",
booktitle = "Proceedings of 7th World Conference on Photovoltaic Energy Conversion",
publisher = "IEEE",
address = "United States",

}

Mantel, C, Spataru, S, Parikh, H, Sera, D, Benatto, GADR, Riedel, N, Thorsteinsson, S, Poulsen, PB & Forchhammer, S 2018, Correcting for Perspective Distortion in Electroluminescence Images of Photovoltaic Panels. in Proceedings of 7th World Conference on Photovoltaic Energy Conversion . IEEE, 7th World Conference on Photovoltaic Energy Conversion , Waikoloa, United States, 10/06/2018. https://doi.org/10.1109/PVSC.2018.8547724

Correcting for Perspective Distortion in Electroluminescence Images of Photovoltaic Panels. / Mantel, Claire; Spataru, Sergiu; Parikh, Harsh; Sera, Dezso; Benatto, Gisele Alves dos Reis; Riedel, Nicholas; Thorsteinsson, Sune; Poulsen, Peter Behrensdorff; Forchhammer, Søren.

Proceedings of 7th World Conference on Photovoltaic Energy Conversion . IEEE, 2018.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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T1 - Correcting for Perspective Distortion in Electroluminescence Images of Photovoltaic Panels

AU - Mantel, Claire

AU - Spataru, Sergiu

AU - Parikh, Harsh

AU - Sera, Dezso

AU - Benatto, Gisele Alves dos Reis

AU - Riedel, Nicholas

AU - Thorsteinsson, Sune

AU - Poulsen, Peter Behrensdorff

AU - Forchhammer, Søren

PY - 2018

Y1 - 2018

N2 - With the significant growth in the number of photovoltaic (PV) installations and their size, regular PV system inspection has become a challenge. Aerial drone imaging, based on visual, thermographic, and more recently luminescence, can be viable solutions for PV inspection. However, to achieve effective detection and quantification of failure based on images acquired form Unmanned Aerial Vehicle, there is need for image quality enhancement and correction of distortions, inherent to the drone measurement process. In this work we propose methods to automatically correct the perspective distortion in electroluminescent (EL) images of PV panels. We identified two main cases of perspective distortion: when the imaging plane is parallel to the panel plane or not, and propose methods to correct both. For both cases, theproposed method yields good results, as assessed by visual evaluation.

AB - With the significant growth in the number of photovoltaic (PV) installations and their size, regular PV system inspection has become a challenge. Aerial drone imaging, based on visual, thermographic, and more recently luminescence, can be viable solutions for PV inspection. However, to achieve effective detection and quantification of failure based on images acquired form Unmanned Aerial Vehicle, there is need for image quality enhancement and correction of distortions, inherent to the drone measurement process. In this work we propose methods to automatically correct the perspective distortion in electroluminescent (EL) images of PV panels. We identified two main cases of perspective distortion: when the imaging plane is parallel to the panel plane or not, and propose methods to correct both. For both cases, theproposed method yields good results, as assessed by visual evaluation.

U2 - 10.1109/PVSC.2018.8547724

DO - 10.1109/PVSC.2018.8547724

M3 - Article in proceedings

SN - 9781538685297

BT - Proceedings of 7th World Conference on Photovoltaic Energy Conversion

PB - IEEE

ER -

Mantel C, Spataru S, Parikh H, Sera D, Benatto GADR, Riedel N et al. Correcting for Perspective Distortion in Electroluminescence Images of Photovoltaic Panels. In Proceedings of 7th World Conference on Photovoltaic Energy Conversion . IEEE. 2018 https://doi.org/10.1109/PVSC.2018.8547724