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1 Annals of Computer Science and Information Systems

1 2024

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A bottom-up approach to select constrained spectral bands discriminating vine diseases

Zhang Shurong, Goupil Alban, Vrabie Valeriu, Perrin Eric, Panon Marie-Laure

Annals of Computer Science and Information Systems

2024

Vol. 39

707--712

The detection and control of diseases constitute a primary objective of French viticultural research. In this paper, we present a bottom-up hierarchical approach for selecting spectral bands suitable for class discrimination of spectra acquired by Infrared spectroscopy. Our method entails evaluating neighbouring bands using various similarity metrics, applying aggregation criteria, and ultimately identifying a limited number of the most relevant bands for the separation of classes. The bandwidths are limited within a range as is typically required for choosing existing optical filters or specifying coloured filter arrays. Our approach facilitates the discovery of distinctive spectral bands associated with a disease of interest, enabling the customization of multispectral cameras to meet specific requirements. It was applied to spectra collected on vine leaves spanning a three-year period with the goal to identify the most discriminant bands for the detection of grapevine yellows. The results show that a limited number of bands are sufficient to identify this class of interest through a classifier based on Linear Discriminant Analysis.