{"title":"视频图像处理中使用背景减法对运动目标进行检测和分割","authors":"Anaswara S, Mohan Resmi","doi":"10.1109/COMPSC.2014.7032664","DOIUrl":null,"url":null,"abstract":"Moving objects often contain almost important information for surveillance videos, traffic monitoring, human motion capture etc. Background subtraction methods are widely exploited for moving object detection in videos in many applications. Moving object segmentation is the application in video processing. Segmentation helps in detecting various features of moving objects for further video/image processing. In this paper object detection and segmentation is proposed and they are compared using background subtraction algorithm (object detection) and segmentation algorithm (edge detection and thresholding). The experiment results show that the proposed method gives better results.","PeriodicalId":388270,"journal":{"name":"2014 First International Conference on Computational Systems and Communications (ICCSC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"Video image processing for moving object detection and segmentation using background subtraction\",\"authors\":\"Anaswara S, Mohan Resmi\",\"doi\":\"10.1109/COMPSC.2014.7032664\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Moving objects often contain almost important information for surveillance videos, traffic monitoring, human motion capture etc. Background subtraction methods are widely exploited for moving object detection in videos in many applications. Moving object segmentation is the application in video processing. Segmentation helps in detecting various features of moving objects for further video/image processing. In this paper object detection and segmentation is proposed and they are compared using background subtraction algorithm (object detection) and segmentation algorithm (edge detection and thresholding). The experiment results show that the proposed method gives better results.\",\"PeriodicalId\":388270,\"journal\":{\"name\":\"2014 First International Conference on Computational Systems and Communications (ICCSC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 First International Conference on Computational Systems and Communications (ICCSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPSC.2014.7032664\",\"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 First International Conference on Computational Systems and Communications (ICCSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSC.2014.7032664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video image processing for moving object detection and segmentation using background subtraction
Moving objects often contain almost important information for surveillance videos, traffic monitoring, human motion capture etc. Background subtraction methods are widely exploited for moving object detection in videos in many applications. Moving object segmentation is the application in video processing. Segmentation helps in detecting various features of moving objects for further video/image processing. In this paper object detection and segmentation is proposed and they are compared using background subtraction algorithm (object detection) and segmentation algorithm (edge detection and thresholding). The experiment results show that the proposed method gives better results.