In the past years, the development of μLED arrays gained momentum since they combine the advantages of μLEDs, such as high brightness and longevity, with a high resolution of a micro-scaled structure. For the development, spatially resolved measurements of luminance and color of single μLEDs and the entire light-emitting surface are analyzed as they are crucial for the visual perception. However, the former is time intense in measurement and evaluation, and the latter suffers from interference caused by nonfunctional μLEDs. This paper presents a method to perform both analyzes with a single measurement using unsupervised machine learning. The results suggest that a precious reconstruction of the μLEDs and a more accurate characterization μLED arrays can be achieved.
@article{arxiv.2011.05155,
title = {Machine learning based luminance analysis of a $\mu$LED array},
author = {Steven Becker},
journal= {arXiv preprint arXiv:2011.05155},
year = {2021}
}