Spherical coordinates framed RGB color space dichromatic reflection model based image segmentation: Application to wildland fires' outlines extraction

V. Amarger, D. Ramík, C. Sabourin, K. Madani, Ramón Moreno, L. Rossi, M. Graña
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引用次数: 1

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.
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基于球坐标框架RGB色彩空间二色反射模型的图像分割:在野火轮廓提取中的应用
野火是世界上许多国家面临的主要风险。为了高效灭火,火锋传播的建模和预测是迫切需要的。然而,野火涉及复杂的动力学,对这种复杂系统的数学建模需要从实际情况中提取可靠的信息,这远非一项微不足道的任务。人工视觉和图像处理为可靠地提取所需信息提供了诱人的潜力。在本文中,我们关注火焰和火焰的分割,处理上述已经开放的问题。我们提出的分割方法是基于对RGB色彩空间的球面解释重新制定的二色反射模型。
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Case study: Deployment of the 2D NoC on 3D for the generation of large emulation platforms A combining approach for 2D face recognition application on IV2 database Spherical coordinates framed RGB color space dichromatic reflection model based image segmentation: Application to wildland fires' outlines extraction Image processing and vision for the study and the modeling of spreading fires Real time watermarking to authenticate the WSQ bitstream
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