Multi-spectral material classification in landscape scenes using commodity hardware - Bradbury, Gwyneth; Mitchell, Kenny; Weyrich, Tim (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013)
We investigate the advantages of a stereo, multi-spectral acquisition system for material classification in ground-level landscape images. Our novel system allows us to acquire high-resolution, multi-spectral stereo pairs using commodity photographic equipment. Given additional spectral information we obtain better classification of vegetation classes than the standard RGB case. We test the system in two modes: splitting the visible spectrum into six bands; and extending the recorded spectrum to near infra-red. Our six-band design is more practical than standard multi-spectral techniques and foliage classification using acquired images compares favourably to using a standard camera. © 2013 Springer-Verlag.
CRIS-Team Scopus Importer:2022-07-26
Keywords: foliage classification; Material classification; multi-spectral imaging