On the evaluation of segmentation methods for wildland fire

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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. © 2009 Springer Berlin Heidelberg.

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Rudz, S., Chetehouna, K., Hafiane, A., Sero-Guillaume, O., & Laurent, H. (2009). On the evaluation of segmentation methods for wildland fire. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5807 LNCS, pp. 12–23). https://doi.org/10.1007/978-3-642-04697-1_2

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