| 基于SVM和模糊免疫网络的交通标志图像识别 |
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| 引用本文： | 罗晓萍,蒋加伏,唐贤瑛.基于SVM和模糊免疫网络的交通标志图像识别[J].计算机工程与设计,2006,27(9):1542-1544. |
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| 作者姓名： | 罗晓萍 蒋加伏 唐贤瑛 |
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| 作者单位： | 1. 长沙理工大学,计算机与通信工程学院,湖南,长沙,410076;安徽师范大学,数学计算机科学学院,安徽,合肥,24100
2. 长沙理工大学,计算机与通信工程学院,湖南,长沙,410076 |
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| 基金项目： | 浙江省湖州市自然科学基金;湖南省教育科学规划项目 |
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| 摘 要： | 提出了一种检测和识别交通标志的方法.该方法根据交通标志的颜色和形状,利用支持向量机的非线性分类能力将其图像区域从实景图像中检测和提取出来,然后利用具有多样性、较强容噪能力的模糊免疫网络来识别.使用不同环境下的实景图像进行实验,结果证明本方法具有平移、旋转、缩放、拉伸不变性和较强的容噪能力.
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| 关 键 词： | 交通标志 图像识别 支持向量机 模糊免疫网络 |
| 文章编号： | 1000-7024（2006）09-1542-03 |
| 收稿时间： | 2005-04-19 |
| 修稿时间： | 2005-04-19 |
Recognition of traffic sign images based on support vector machine and fuzzy immune networks |
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| LUO Xiao-ping,JIANG Jia-fu,TANG Xian-ying.Recognition of traffic sign images based on support vector machine and fuzzy immune networks[J].Computer Engineering and Design,2006,27(9):1542-1544. |
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| Authors: | LUO Xiao-ping JIANG Jia-fu TANG Xian-ying |
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| Affiliation: | 1. Institute of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410076, China; 2. School of Mathematics and Computer Science, Anhui Normal University, Hefei 241000, China |
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| Abstract: | A detection and recognition method for traffic signs are presented. Traffic sign regions are detected and extracted from real world scenes on the basis of their color and shape features using non-linear classification capability of support vector machine, then recognized by fuzzy immune networks which has diversity and well tolerating noise capability. Using real road images in different environment conditions, experimental results show that the method has affine invariability of translation, rotation, scale, distortion and can well tolerating noise. |
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| Keywords: | traffic signs image recognition support vector machine fuzzy immune networks |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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