Fu, Zhouyu; Robles-Kelly, Antonio
In this paper, we develop a novel approach to object-material identification in spectral imaging by combining the use of invariant spectral absorption features and statistical machine-learning techniques. Our method hinges on the relevance of spectral absorption features for material identification and casts the problem into a pattern-recognition setting by making use of an invariant representation of the most discriminant band segments in the spectra. Thus, here, we view the identification...[Show more]
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