基于adaboost和svm的交通标志识别研究与实现大学生毕业论文（设计）.doc

硕士学位论文 基于AdaBoost和SVM的交通标志识别研究与实现 Research and Implementation of Traffic Sign Recognition Based on Adaboost and SVM 论文题目：基于AdaBoost和SVM的交通标志识别研究与实现经过国内外学者年研究，交通标志识别理论和体系取得了突破性的进展。光照、，一种变的AdaBoost综合颜色和形状的交通标志检测方法子模式组合的特征提取方法在子模式的基础上，对比了相邻分块、交叠边缘分块和滑动分块基于径向基核函数的支持向量机分类器相结合的识别方法表明，AdaBoost和SVM的交通标志的识别方法识别效果更好，识别率更高关 键 词：交通标志识别，分块核函数，SVM，AdaBoost 论文类型：应用研究 Title： Research andof Traffic Sign Recognition Based on Adaboost and SVM Specialty：Computer Science and Technology Applicant： Supervisor：Prof.Xianglin Miao Traffic sign recognition is an important part of intelligent traffic signs. It involves many kinds of the technology such as sensor technology, information technology, automation technology and computer technology, and how to identify road, identification of collision, identify the object recognition of traffic signs, etc. After years of research of scholars both at home and abroad, and traffic sign recognition theory and technology system has made breakthrough progress. therefore, the image collection is the first step to realize intelligent transportation, it is very important to the follow-up of the manipulation, but the traffic signs are all exposed to special outdoor environment, to make the drivers see all kinds of traffic signs, traffic signs usually should be placed beside the road and pipe bend. Where traffic signs are often vulnerable to affect by the strong light, dust and various trees, so the sharpness of image is bad, which affect the camera collection, the cars embedded computer software and hardware system of image information is ambiguous. Because of this, people have been trying to research how to improve the traffic sign image recognition. This paper has discussed some related research how to improve the recognition rate of traffic sign, although the research results have a considerable distance from the practical, but its research process broads the horizons, increases of knowledge, improves the level of the business. The research contents of