Image based fog detection in vehicles

M. Pavlic, H. Belzner, G. Rigoll, Slobodan Ilic
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引用次数: 80

Abstract

Modern vehicles are equipped with many cameras and their use in many practical applications is extensive. Detecting the presence of fog from images of a camera mounted in vehicles is a very challenging task with the potential to be used in many practical applications. Approaches introduced until now analyze properties of local objects in the image like lane markings, traffic signs, back lights of vehicles in front or head lights of approaching vehicles. By contrast to all these related works we propose to use image descriptors and a classification procedure in order to distinguish images with fog present from those free of fog. These image descriptors are global and describe the entire image using Gabor filters at different frequencies, scales and orientations. Our experiments demonstrated hight potential of the proposed method for fog detection on daytime images.
基于图像的车辆雾检测
现代车辆配备了许多摄像头,它们在许多实际应用中的用途是广泛的。从安装在车辆上的摄像头的图像中检测雾的存在是一项非常具有挑战性的任务,具有许多实际应用的潜力。目前引入的方法是分析图像中局部物体的属性,如车道标记、交通标志、前方车辆的后灯或驶近车辆的前灯。在此基础上,提出了利用图像描述符和分类方法来区分有雾和无雾图像的方法。这些图像描述符是全局的,使用Gabor滤波器在不同的频率、尺度和方向上描述整个图像。我们的实验证明了该方法在日间图像的雾检测中具有很高的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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