Multispectral Imaging for Material Analysis in an Outdoor Environment Using Normalized Cuts

Abstract

Multispectral imaging has promising and wide application areas, including medical imaging, remote sensing, and cultural asset preservation. In particular, cultural assets are often damaged by microorganisms such as moss and mold. Thus, asset preservation requires measuring the kinds and extent of microorganisms by obtaining spectral information in wide areas. This process requires developing an efficient spectral sensing system that can obtain data for wide areas as well as segmentation methods to identify those locations. This paper describes a new multispectral imaging system applicable to wide areas. Our design allows the system to have a wide field of view of high resolution with low noise and negligible distortion. We can apply this system to measuring the surface spectrum on an object surface in an outdoor environment. For determining the distribution of microorganisms, we developed a multispectral image segmentation method using the data obtained by our system. Finally, we applied our system and segmentation method to the data from the bas-relief of the Bayon Temple in the Angkor ruin, and we identified the classes and distribution areas of the microorganisms.

Cite

Text

Morimoto and Ikeuchi. "Multispectral Imaging for Material Analysis in an Outdoor Environment Using Normalized Cuts." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457515

Markdown

[Morimoto and Ikeuchi. "Multispectral Imaging for Material Analysis in an Outdoor Environment Using Normalized Cuts." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/morimoto2009iccvw-multispectral/) doi:10.1109/ICCVW.2009.5457515

BibTeX

@inproceedings{morimoto2009iccvw-multispectral,
  title     = {{Multispectral Imaging for Material Analysis in an Outdoor Environment Using Normalized Cuts}},
  author    = {Morimoto, Tetsuro and Ikeuchi, Katsushi},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2009},
  pages     = {1909-1916},
  doi       = {10.1109/ICCVW.2009.5457515},
  url       = {https://mlanthology.org/iccvw/2009/morimoto2009iccvw-multispectral/}
}