{"title":"先进交通信号控制中车辆的实时检测","authors":"C. Han, Qinyu Zhang","doi":"10.1109/ICCEE.2008.126","DOIUrl":null,"url":null,"abstract":"Vehicle detection by video cameras is one of the most promising new technologies for wireless large-scale data collection and implementation of advanced traffic control and management schemes such as vehicle guidance/navigation. In this paper we propose an approach to detect and count vehicles at an intersection in real-time, using a fixed camera. After identifying moving objects images via background frame differencing, edge detection, erosion and dilation operations are performed to suppress noise. Separated and rotated properly, the denoised binary image is then used to generate a vertical projection histogram from which information about the size and coordinates of each component is utilized to compute the number of vehicles. This detection algorithm gives an approximate number of vehicles. An adaptive traffic signal control strategy controls the traffic flow. The simulating results show a great efficiency of traffic control and management scheme in practice.","PeriodicalId":365473,"journal":{"name":"2008 International Conference on Computer and Electrical Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Real-Time Detection of Vehicles for Advanced Traffic Signal Control\",\"authors\":\"C. Han, Qinyu Zhang\",\"doi\":\"10.1109/ICCEE.2008.126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicle detection by video cameras is one of the most promising new technologies for wireless large-scale data collection and implementation of advanced traffic control and management schemes such as vehicle guidance/navigation. In this paper we propose an approach to detect and count vehicles at an intersection in real-time, using a fixed camera. After identifying moving objects images via background frame differencing, edge detection, erosion and dilation operations are performed to suppress noise. Separated and rotated properly, the denoised binary image is then used to generate a vertical projection histogram from which information about the size and coordinates of each component is utilized to compute the number of vehicles. This detection algorithm gives an approximate number of vehicles. An adaptive traffic signal control strategy controls the traffic flow. The simulating results show a great efficiency of traffic control and management scheme in practice.\",\"PeriodicalId\":365473,\"journal\":{\"name\":\"2008 International Conference on Computer and Electrical Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Computer and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEE.2008.126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Computer and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEE.2008.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-Time Detection of Vehicles for Advanced Traffic Signal Control
Vehicle detection by video cameras is one of the most promising new technologies for wireless large-scale data collection and implementation of advanced traffic control and management schemes such as vehicle guidance/navigation. In this paper we propose an approach to detect and count vehicles at an intersection in real-time, using a fixed camera. After identifying moving objects images via background frame differencing, edge detection, erosion and dilation operations are performed to suppress noise. Separated and rotated properly, the denoised binary image is then used to generate a vertical projection histogram from which information about the size and coordinates of each component is utilized to compute the number of vehicles. This detection algorithm gives an approximate number of vehicles. An adaptive traffic signal control strategy controls the traffic flow. The simulating results show a great efficiency of traffic control and management scheme in practice.