Thermal image segmentation by K -means clustering algorithm
The HSV, CMY, NTSC, YCbCr color spaces are not well suited for describing colors in terms that one practical for human interpretation. So, the RGB thermal image has to be converted into HIS image for better visibility to indentify the defects presented in the panel. and apply the K -means clustering algorithm to segment the image and diagnose the defects in the PV panel
Reference:
Uma, J., Muniraj, C., and Sathya, N., "Diagnosis of Photovoltaic (PV) Panel Defects Based on Testing and Evaluation of Thermal Image," Journal of Testing and Evaluation, https://doi.org/10.1520/JTE20170653. ISSN 0090-3973.
Cite As
Muniraj c (2024). Thermal image segmentation by K -means clustering algorithm (https://www.mathworks.com/matlabcentral/fileexchange/69175-thermal-image-segmentation-by-k-means-clustering-algorithm), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
- Image Processing and Computer Vision > Computer Vision Toolbox > Point Cloud Processing > Display Point Clouds >
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.