{"title":"移动车辆检测技术研究","authors":"Jin Mei-shan, Meng Qing-hui, Huang Fei, Li Jing","doi":"10.1109/CECNET.2012.6201424","DOIUrl":null,"url":null,"abstract":"This paper introduces the Comprehensive utilization of symmetric difference methods and background subtraction[1, 2] for moving vehicle detection. Firstly build a reliable background update model, and then combine the basically accurate foreground image got from background subtraction with difference image got from symmetric difference. Finally get the reliable image of moving target, so that the mobile vehicles can be detected from video sequence.","PeriodicalId":135557,"journal":{"name":"2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research on the moving vehicle detection technology\",\"authors\":\"Jin Mei-shan, Meng Qing-hui, Huang Fei, Li Jing\",\"doi\":\"10.1109/CECNET.2012.6201424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces the Comprehensive utilization of symmetric difference methods and background subtraction[1, 2] for moving vehicle detection. Firstly build a reliable background update model, and then combine the basically accurate foreground image got from background subtraction with difference image got from symmetric difference. Finally get the reliable image of moving target, so that the mobile vehicles can be detected from video sequence.\",\"PeriodicalId\":135557,\"journal\":{\"name\":\"2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CECNET.2012.6201424\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CECNET.2012.6201424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on the moving vehicle detection technology
This paper introduces the Comprehensive utilization of symmetric difference methods and background subtraction[1, 2] for moving vehicle detection. Firstly build a reliable background update model, and then combine the basically accurate foreground image got from background subtraction with difference image got from symmetric difference. Finally get the reliable image of moving target, so that the mobile vehicles can be detected from video sequence.
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