Title :
Fire scene segmentations for forest fire characterization: A comparative study
Author :
Collumeau, Jean-François ; Laurent, Hélène ; Hafiane, Adel ; Chetehouna, Khaled
Author_Institution :
Lab. PRISME UPRES EA 4229 88, ENSI de Bourges, Bourges, France
Abstract :
Forest fires constitute one of the most damaging natural disaster for many countries around the world. Its mechanisms can be studied through forest fire metrology. Despite a large number of proposed algorithms for fire detection, only few works adress the segmentation problem in fire metrology. The main purpose of this paper is to introduce a SVM-based segmentation method for forest fire metrology. This method is confronted with state-of-the-art fire segmentation algorithms using supervised evaluation criteria and an ad hoc expertised picture database. The obtained results highlight the good performances of the proposed method compared to prior algorithms.
Keywords :
disasters; fires; forestry; image segmentation; support vector machines; visual databases; SVM-based segmentation method; ad hoc expertised picture database; fire detection; fire scene segmentation problem; forest fire characterization; forest fire metrology; natural disaster; state-of-the-art fire segmentation algorithm; supervised evaluation criteria; Databases; Fires; Image color analysis; Image segmentation; Measurement; Metrology; Support vector machines; Forest fire metrology; Support Vector Machine; fire segmentation; supervised evaluation;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6116285