On the Evaluation of Segmentation Methods for Wildland Fire
Identifieur interne : 000661 ( Main/Exploration ); précédent : 000660; suivant : 000662On the Evaluation of Segmentation Methods for Wildland Fire
Auteurs : Steve Rudz [France] ; Khaled Chetehouna [France] ; Adel Hafiane [France] ; Olivier Sero-Guillaume [France] ; Hélène Laurent [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2009.
Abstract
Abstract: This paper focuses on the study of fire color spaces and the evaluation of image segmentation methods commonly available in the literature of wildland and urban fires. The evaluation method, based on the determination of a segmentation quality index, is applied on three series of fire images obtained at the usual scales of validation of forest fire models (laboratory scale, fire tunnel scale and field scale). Depending on the considered scale, different methods reveal themselves as being the most appropriate. In this study we present the advantages and drawbacks of different segmentation algorithms and color spaces used in fire detection and characterization.
Url:
DOI: 10.1007/978-3-642-04697-1_2
Affiliations:
- France
- Centre-Val de Loire, Grand Est, Lorraine (région), Région Centre
- Bourges, Vandoeuvre les Nancy
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<front><div type="abstract" xml:lang="en">Abstract: This paper focuses on the study of fire color spaces and the evaluation of image segmentation methods commonly available in the literature of wildland and urban fires. The evaluation method, based on the determination of a segmentation quality index, is applied on three series of fire images obtained at the usual scales of validation of forest fire models (laboratory scale, fire tunnel scale and field scale). Depending on the considered scale, different methods reveal themselves as being the most appropriate. In this study we present the advantages and drawbacks of different segmentation algorithms and color spaces used in fire detection and characterization.</div>
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