Suresh Babu Changalasetty, Ahmed S. Badawy, Wade Ghribi, Lalitha Saroja Thota
{"title":"LabVIEW中移动车辆的识别与特征提取","authors":"Suresh Babu Changalasetty, Ahmed S. Badawy, Wade Ghribi, Lalitha Saroja Thota","doi":"10.1109/ICCSP.2014.6950172","DOIUrl":null,"url":null,"abstract":"In recent years, video monitoring and surveillance systems have been widely used in traffic management. The image sequences for traffic scenes are recorded by a stationary camera. The video clip is sent to LabVIEW program to convert into image frames. NI LabVIEW vision assistant module is used to detect the moving vehicle. The method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Background subtraction is used which improves the adaptive background mixture model and makes the system learn faster and more accurately, as well as adapt effectively to changing environments. The resulting system robustly identifies vehicles, rejecting background and tracks vehicles over a specific period of time. Once the (object) vehicle is tracked, the attributes of the vehicle like width, length, perimeter, area etc are extracted by image process feature extraction techniques. In proposed system we use LabVIEW and Vision assistant module for image processing and feature extraction. The project will benefit to reduce cost of traffic monitoring system and complete automation of traffic monitoring system.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Identification and feature extraction of moving vehicles in LabVIEW\",\"authors\":\"Suresh Babu Changalasetty, Ahmed S. Badawy, Wade Ghribi, Lalitha Saroja Thota\",\"doi\":\"10.1109/ICCSP.2014.6950172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, video monitoring and surveillance systems have been widely used in traffic management. The image sequences for traffic scenes are recorded by a stationary camera. The video clip is sent to LabVIEW program to convert into image frames. NI LabVIEW vision assistant module is used to detect the moving vehicle. The method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Background subtraction is used which improves the adaptive background mixture model and makes the system learn faster and more accurately, as well as adapt effectively to changing environments. The resulting system robustly identifies vehicles, rejecting background and tracks vehicles over a specific period of time. Once the (object) vehicle is tracked, the attributes of the vehicle like width, length, perimeter, area etc are extracted by image process feature extraction techniques. In proposed system we use LabVIEW and Vision assistant module for image processing and feature extraction. The project will benefit to reduce cost of traffic monitoring system and complete automation of traffic monitoring system.\",\"PeriodicalId\":149965,\"journal\":{\"name\":\"2014 International Conference on Communication and Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Communication and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2014.6950172\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Communication and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSP.2014.6950172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification and feature extraction of moving vehicles in LabVIEW
In recent years, video monitoring and surveillance systems have been widely used in traffic management. The image sequences for traffic scenes are recorded by a stationary camera. The video clip is sent to LabVIEW program to convert into image frames. NI LabVIEW vision assistant module is used to detect the moving vehicle. The method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Background subtraction is used which improves the adaptive background mixture model and makes the system learn faster and more accurately, as well as adapt effectively to changing environments. The resulting system robustly identifies vehicles, rejecting background and tracks vehicles over a specific period of time. Once the (object) vehicle is tracked, the attributes of the vehicle like width, length, perimeter, area etc are extracted by image process feature extraction techniques. In proposed system we use LabVIEW and Vision assistant module for image processing and feature extraction. The project will benefit to reduce cost of traffic monitoring system and complete automation of traffic monitoring system.