Rear-Lamp Vehicle Detection and Tracking in Low-Exposure Color Video for Night Conditions
Rear-Lamp Vehicle Detection and Tracking in Low-Exposure Color Video for Night Conditions
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DOI：
10.1109/tits.2010.2045375
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发表时间：
2010-06-01
影响因子：
8.5
通讯作者：
Glavin, Martin
中科院分区：
文献类型：
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作者：
O'Malley, Ronan;Jones, Edward;Glavin, Martin
自动检测前方车辆是许多高级驾驶辅助系统（ADAS）的组成部分，例如碰撞缓解、自动巡航控制（ACC）和自动前照灯调光。提出了一种新的图像处理系统来检测和跟踪汽车尾灯对在前向彩色视频。使用具有互补金属氧化物半导体（CMOS）传感器和拜耳红-绿-蓝（RGB）滤色器的标准低成本照相机，并且该标准低成本照相机可以用于全色图像显示或其他彩色图像处理应用。视频和图像中尾灯的外观可能会发生显着变化，具体取决于摄像头硬件;因此，我们建议采用摄像头配置过程，优化尾灯的外观以进行分割。使用红色阈值从低曝光的前向彩色视频中分割后向灯。与该领域以前使用主观颜色阈值边界的工作不同，我们的颜色阈值直接来自汽车法规，并适用于色调-饱和度-值（HSV）颜色空间中的现实条件。使用颜色互相关对称分析配对灯，并使用卡尔曼滤波跟踪。引入基于跟踪的检测阶段以提高鲁棒性并处理由其他光源和透视失真引起的失真，这在汽车环境中是常见的。结果表明，该系统的高检测率，工作距离，和不同的照明条件和道路环境的鲁棒性。
Automated detection of vehicles in front is an integral component of many advanced driver-assistance systems (ADAS), such as collision mitigation, automatic cruise control (ACC), and automatic headlamp dimming. We present a novel image processing system to detect and track vehicle rear-lamp pairs in forward-facing color video. A standard low-cost camera with a complementary metal-oxide semiconductor (CMOS) sensor and Bayer red-green-blue (RGB) color filter is used and could be utilized for full-color image display or other color image processing applications. The appearance of rear lamps in video and imagery can dramatically change, depending on camera hardware; therefore, we suggest a camera-configuration process that optimizes the appearance of rear lamps for segmentation. Rear-facing lamps are segmented from low-exposure forward-facing color video using a red-color threshold. Unlike previous work in the area, which uses subjective color threshold boundaries, our color threshold is directly derived from automotive regulations and adapted for real-world conditions in the hue-saturation-value (HSV) color space. Lamps are paired using color cross-correlation symmetry analysis and tracked using Kalman filtering. A tracking-based detection stage is introduced to improve robustness and to deal with distortions caused by other light sources and perspective distortion, which are common in automotive environments. Results that demonstrate the system's high detection rates, operating distance, and robustness to different lighting conditions and road environments are presented.