Using Image Processing Techniques for Automated Detection and Annotation of Faulty Regions in Thermal Infrared Images of PV Modules


With the increasingly growing number of solar energy sites, the need for better and faster fault detection techniques becomes more pressing. Using IR imaging is reliable and effective but scanning thousands or even hundreds of thousands of PV modules in mega sites quickly turns to be a time consuming and tedious task. To save on the spent effort and time digital image processing techniques can be introduced into the inspection process to help identify and annotate defects in the thermal footage of PV modules in an automated manner. The methodology used in the paper relies on analyzing the histogram to choose a suitable thresholding point that would help isolate the potential faulty areas in a grayscale IR image.

BY Atilla ErgĀ¼zen | Muhammet Sait “Using Image Processing Techniques for Automated Detection and Annotation of Faulty Regions in Thermal Infrared Images of PV Modules”

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd29749.pdf

Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/29749/using-image-processing-techniques-for-automated-detection-and-annotation-of-faulty-regions-in-thermal-infrared-images-of-pv-modules/atilla-erg%C3%Bczen

special issue publication, open access journal of engineering, call for paper science




Using Image Processing Techniques for Automated Detection and Annotation of Faulty Regions in Thermal Infrared Images of PV Modules IEEE PAPER





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