摘要
提出一种结合常规几何参数及利用亮度、颜色四重阈值进行汽车尾灯检测的算法,以应用于夜间条件下智能汽车追尾预警系统。该算法利用亮度低阈值确定汽车尾灯的疑似区域,利用常规几何参数对上述疑似尾灯区域进行排除,利用红色比例低阈值和亮点比例阈值检测出亮度较高尾灯光斑,利用红色比例高阈值检测出亮度较低的尾灯光斑。实验结果表明,该算法可以快速、准确地检测出夜间的汽车尾灯。
This paper proposes a new vehicle taillights detection algorithm for the night view rear-end collision alarm system of smart vehicle. The algorithm combines with routine geometry parameters, makes use of four thresholds of brightness and color to detect vehicle taillights. The TB_L is used to locate the suspected taillights facular areas, the routine geometry parameters are employed to check and eliminate the suspected taillights facular areas, the TRPL and TBP are adopted to determine the facular areas of bright taillights, the TRP_H is used to determine the facular areas of dim taillights. Experimental results show that the algorithm can detect taillights accurately and quickly.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第21期202-203,206,共3页
Computer Engineering
关键词
追尾预警系统
夜间尾灯检测
亮度阈值
红色阈值
rear-end collision alarm system
night view taillight detection
brightness threshold
red threshold
