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Vehicle recognition based on multi-mechanism fusion with the fuzzy theory and evidence theory | |
Cao, Jie1,2![]() ![]() ![]() | |
2011-12-01 | |
发表期刊 | Journal of Beijing Institute of Technology (English Edition)
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ISSN | 10040579 |
卷号 | 20期号:SUPPL.1页码:47-54 |
摘要 | A vehicle multi-mechanism recognition method based on fusing the data of radio frequency, video and inductive sensor was proposed for low recognition rate of single method. Through data association, the standard target models were got by inductance signal. For video sensor, feature information of awaiting identifying vehicle was obtained by the methods of adaptive frame difference and coordinate transformation, and then the algorithm of fuzzy pattern recognition was employed for matching recognition. For inductive sensor, the awaiting identifying vehicle features were extracted based on double coils peak value detection, and the same algorithm was applied. For radio frequency, the normalized cumulative tag reading rate of each target model was regarded as its likelihood function. Then, the basic probability assignment of each sensor was obtained, and recombined with Dempster-Shafer theory. Simulation results indicate that the vehicle recognition performance by multi-sensor fusion is much better than any single sensor. © Copyright. |
关键词 | Inductive sensors Information fusion Intelligent systems Intelligent vehicle highway systems Pattern recognition Radio waves Vehicles Basic probability assignment Co-ordinate transformation D S evidence theory Dempster-Shafer theory Fuzzy theory Intelligent transportation systems Matching recognition Video identification |
收录类别 | EI |
语种 | 中文 |
出版者 | Beijing Institute of Technology |
EI入藏号 | 20115214650207 |
EI主题词 | Radio frequency identification (RFID) |
EI分类号 | 711 Electromagnetic Waves - 716.3 Radio Systems and Equipment - 723.4 Artificial Intelligence - 723.5 Computer Applications - 732.2 Control Instrumentation - 903.1 Information Sources and Analysis |
来源库 | Compendex |
分类代码 | 711 Electromagnetic Waves - 716.3 Radio Systems and Equipment - 723.4 Artificial Intelligence - 723.5 Computer Applications - 732.2 Control Instrumentation - 903.1 Information Sources and Analysis |
文献类型 | 期刊论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/111675 |
专题 | 电气工程与信息工程学院 计算机与通信学院 |
作者单位 | 1.College of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China; 2.Manufacturing Engineering Technology Research Center of Gansu, Lanzhou 730050, China; 3.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China |
第一作者单位 | 兰州理工大学 |
第一作者的第一单位 | 兰州理工大学 |
推荐引用方式 GB/T 7714 | Cao, Jie,Chen, Ji-Ming,Hou, Liang,et al. Vehicle recognition based on multi-mechanism fusion with the fuzzy theory and evidence theory[J]. Journal of Beijing Institute of Technology (English Edition),2011,20(SUPPL.1):47-54. |
APA | Cao, Jie,Chen, Ji-Ming,Hou, Liang,Wang, Jin-Hua,&Zhang, Mo-Yi.(2011).Vehicle recognition based on multi-mechanism fusion with the fuzzy theory and evidence theory.Journal of Beijing Institute of Technology (English Edition),20(SUPPL.1),47-54. |
MLA | Cao, Jie,et al."Vehicle recognition based on multi-mechanism fusion with the fuzzy theory and evidence theory".Journal of Beijing Institute of Technology (English Edition) 20.SUPPL.1(2011):47-54. |
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