基于红色分割的交通标志检测改进方法

Manal El Baz, T. Zaki, H. Douzi
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引用次数: 1

摘要

红色分割在图像处理特别是交通标志检测中有着广泛的应用。各种光照和天气条件下的色彩分割是一项具有挑战性的任务。这些条件使交通标志的颜色发生了变化。在本文中,我们的目标是提高最先进的方法在RGB和HSV空间的精度。尽管这种最先进的方法效率很高,但RGB空间中的红色分割存在一些假阳性检测,特别是在夜间,而HSV空间中的红色分割以红色像素为感兴趣区域检测黑色像素。为了提高该方法的精度,本文提出将两种分割方法结合起来。我们还提出了改变HSV中红色分割的阈值来去除非红色像素和提取低饱和度的红色像素。此外,我们还对RGB空间中红色分割的阈值进行了一些修改,以提高其性能。实验结果表明,与现有方法相比,该方法在各种光照和天气条件下都能更准确地检测出交通标志的红色。
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An Improved Method for Red Segmentation Based Traffic Sign Detection
The red color segmentation is widely used in image processing especially for traffic sign detection. The color segmentation under variety of light and weather conditions is a challenging task. These conditions make modifications on traffic sign colors. In this paper, we aim to improve the precision of a state-of-the-art method in RGB and HSV spaces. Although the efficiency of this state-of-the-art method, the red segmentation in RGB space has some false positive detections especially at night, and the red segmentation in HSV space detects the black pixels with red pixels as a region of interest. In order to improve the precision of this method, we propose in this paper to combine the two segmentations. We also propose changing the threshold of the red segmentation in HSV to remove non-red pixels and to extract red pixels with low saturation. In addition, we make some modifications on the threshold of the red segmentation in RGB space to improve its performance. The results obtained in experiments show that our method detects more accurately red color of traffic signs under variety of light and weather conditions compared to the state-of-the-art method.
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