A Machine Learning Approach for Material Detection in Hyperspectral Images

Marée, Raphaël; Stevens, Benjamin; Geurts, Pierre; Guern, Yves; Mack, Philippe

doi:10.1109/CVPR.2009.5204119

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A Machine Learning Approach for Material Detection in Hyperspectral Images

Marée, Raphaël; Stevens, Benjamin; Geurts, Pierre et al.

2009 • In Proc. 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (OTCBVS-CVPR09)

Peer reviewed

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https://hdl.handle.net/2268/14710

DOI
10.1109/CVPR.2009.5204119

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Keywords :

image; hyperspectral; extra-trees

Abstract :

[en] In this paper we propose a machine learning approach for the detection of gaseous traces in thermal infra red hyperspectral images. It exploits both spectral and spatial information by extracting subcubes and by using extremely randomized trees with multiple outputs as a classifier. Promising results are shown on a dataset of more than 60 hypercubes.

Disciplines :

Computer science

Author, co-author :

Marée, Raphaël ; Université de Liège - ULiège > GIGA-Management : Plateforme bioinformatique

Stevens, Benjamin ; PEPITE SA

Geurts, Pierre ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Guern, Yves; ATIS SA

Mack, Philippe; PEPITE SA

Language :

English

Title :

A Machine Learning Approach for Material Detection in Hyperspectral Images

Publication date :

2009

Event name :

6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum

Event place :

Miami, United States

Audience :

International

Main work title :

Proc. 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (OTCBVS-CVPR09)

Publisher :

IEEE

Peer reviewed :

Peer reviewed

Additional URL :

http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2009/MSGGM09

Name of the research project :

HAWKEYE SST4-CT-2005-516168

Funders :

F.R.S.-FNRS - Fonds de la Recherche Scientifique
UE - Union Européenne

Available on ORBi :

since 16 June 2009

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Bibliography

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