Abstract
Computer-aided algorithms play a vital role in industrial automation; image
processing algorithms have a wide variety of applications in the detection of defects in
real-time studies. This chapter proposes image processing algorithms for the detection
of defects in solar panel electroluminescent images. This research work proposes a
median filter for the filtering of images followed by a region of interest extraction by
fast fuzzy c-means clustering. The outcome of this work paves the way for researchers
working in the processing of solar panel electroluminescent images for defects
classification.
Keywords: Direct simulation monte carlo, Fractional brownian motion, Knudsen number, Lattice-boltzmann, Mesoscopic methods, Nanoscale pores, Porous media, Rarefied flow, Reconstruction, Slipflow, Transition regime.
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