自然背景中交通标志的检测与识别  

The Detection and Recognition of Traffic Signs in Natural Scenes

作　　者：孙光民[1] 王晶[1] 于光宇[1] 李罡[1] 许磊[1] 

机构地区：[1]北京工业大学电子信息与控制工程学院,北京100124

出　　处：《北京工业大学学报》2010年第10期1337-1343,1395,共8页Journal of Beijing University of Technology

摘　　要：根据我国交通标志的颜色和几何属性,提出了一种适用于自然背景下的交通标志识别系统.该系统采用RGB彩色分量差对自然背景下的交通标志图像进行分割,而后采用先分类后识别的两级神经网络结构,分别提取交通标志的轮廓特征和不变矩特征作为分类网络和识别网络的输入特征,最终对交通标志图像进行分类识别.实验结果证明,该系统能对自然背景下的交通标志图像达到较好的识别效果,并且具有较强的鲁棒性和广泛的适用性.According to color and geometric properties of traffic signs in our country,an efficient traffic sign recognition system applying to natural scenes is proposed in this paper. In this system,an improved image segmentation algorithm based on RGB model is implemented on segmenting traffic signs in natural scenes. Moreover,two level neural networks are used to classify and recognize traffic signs. The outline and invariable moment characteristics are used as the input characteristics of the classification neural network and identification neural network,respectively. The experimental results demonstrate this efficient system can achieve perfect recognization results to traffic signs in natural scences; furthermore,it’s robust and broad applicability.

关 键 词：交通标志 图像分割 神经网络 轮廓特征 不变矩 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]