城市环境中交通信号灯准确识别与状态估计  

Accuracy recognition and state estimation for traffic light in urban environment

作　　者：蔡自兴[1] 谷明琴 

机构地区：[1]中南大学信息科学与工程学院,长沙410083 [2]奇瑞前瞻技术科学院,安徽芜湖241009

出　　处：《控制与决策》2014年第1期163-167,共5页Control and Decision

基　　金：国家自然科学基金项目(90820302;60805027);国家博士点基金项目(195470);湖南省自然科学基金项目(12JJ6058);湖南省院士基金项目(2009FJ4030)

摘　　要：根据交通信号灯灯板颜色和形状定位图像中的灯板位置.将灯板区域的彩色图像转换到YCbCr空间,分割灯板区域中的红、黄、绿三色区域,利用交通信号灯的形态特性定位交通灯位置.用Gabor小波和2维独立分量分析提取感兴趣区域的特征,送入最近邻分类器分类信号灯的类型.用代表性的观测序列建立隐马尔科夫模型,并结合识别和跟踪结果估计信号灯状态.实验结果表明,该算法能可靠、准确地识别出信号灯,并有效地估计出信号灯的状态.The board of traffic light is located in input image by its color and shape. The color image of the board is converted to YCbCr space. The region that includes main color（red, amber, green） is segmented by thresholds. The traffic light is positioned by morphological properties. The feature of region of interest（RoI） is extracted by Gabor wavelet and 2 dimension independent component analysis, and sent into the nearest neighbor classifier to classify the type of traffic light. Structures of hidden Markov model are built by several representative observation sequences. The current state of traffic light is estimated by hidden Markov model which combines with recognition and tracking results. The experimental results show that this algorithm can recognize and track the traffic lights reliably and accurately, and estimate the states of the traffic light effectively.

关 键 词：交通信号灯检测 交通信号灯识别 Kalman跟踪 隐马尔科夫模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]