Towards Automatic Butterfly Species Recognition Using a Single Spatio-Hyperspectral Image - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

Towards Automatic Butterfly Species Recognition Using a Single Spatio-Hyperspectral Image

Résumé

Butterfly Species identification accounts nowadays for a challenge to evaluate the biodiversity state. Using special compact Hyperspectral Cameras for this task is more attractive. Whereas usual techniques use a sequence of images to compute a datacube, we focus here on a single image resulting in a partial butterfly datacube. With a pre identification of the features from a butterfly library, we propose combined probabilistic clustering technique based on a weighted combination of Z-score and Gaussian Naive Bayes probability which aims to recognize the associated cluster from the particular butterfly species. Results obtained in this context achieve good performance with respect to Gaussian Naive Bayes probability or Z-score-based techniques.
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vendredi 1 novembre 2024
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Dates et versions

hal-04605762 , version 1 (03-10-2024)

Identifiants

  • HAL Id : hal-04605762 , version 1

Citer

Erick Adje, Gilles Delmaire, Arnaud Ahouandjinou, Matthieu Puigt, Gilles Roussel. Towards Automatic Butterfly Species Recognition Using a Single Spatio-Hyperspectral Image. 32nd European Signal Processing Conference (EUSIPCO'24), Aug 2024, Lyon, France. pp.1252-1256. ⟨hal-04605762⟩
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