Title :
Spherical coordinates framed RGB color space dichromatic reflection model based image segmentation: Application to wildland fires´ outlines extraction
Author :
Amarger, V. ; Ramik, Dominik Maximilian ; Sabourin, Christophe ; Madani, Kurash ; Moreno, R. ; Rossi, L. ; Grana, Manuel
Author_Institution :
Signals, Images, & Intell. Syst. Lab., Univ. Paris-Est Creteil (UPEC), Lieusaint, France
Abstract :
Wildland fires represent a major risk for many countries over the world. For efficient fire fighting, the modeling and prediction of fire front propagation is a curial need. However, wildland fires´ involves complex dynamics and mathematical modelling of such complex systems needs reliable information extraction from real situations, which is far from being a trivial task. Artificial Vision and Image Processing offer appealing potential toward reliable extraction of required information. In this paper we focus on flames´ and fires´ segmentation, dealing with the above-stated already open problem. The segmentation approach that we propose is based on dichromatic reflection model reformulated on a spherical interpretation of the RGB color space.
Keywords :
computer vision; environmental science computing; image colour analysis; image segmentation; wildfires; RGB color space dichromatic reflection model; RGB color space spherical interpretation; artificial vision; fire fighting; fire front propagation modeling; fire front propagation prediction; fire segregation; flame segregation; image processing; image segmentation; red-green-blue color model; wildland fire outline extraction; Combustion; Fires; Image color analysis; Image segmentation; Laboratories; Reflection; Vectors; Dichromatic Reflection Model; RGB color space; Salient vision; Segmentation; Spherical; Wildland fires;
Conference_Titel :
Image Processing Theory, Tools and Applications (IPTA), 2012 3rd International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2585-1
DOI :
10.1109/IPTA.2012.6469529