{"title":"Animal tracking using background subtraction on multi threshold segmentation","authors":"E. Surendar, Vimin M Thomas, A. Mary Posonia","doi":"10.1109/ICCPCT.2016.7530223","DOIUrl":null,"url":null,"abstract":"The proposed project performs motion detection and animal tracking based on background subtraction using multi threshold approach with mathematical morphology. Here the techniques frame differences; multi threshold based detection will be used. Along with this multi threshold, mathematical morphology also used which has an ability to attenuate color variations produced by background motions which will highlight moving objects. After the object foreground detection, the parameters like animal or human will be detected. Finally the simulated results will be shown. It will use approximate method with mathematical morphology approach rather than prior background subtraction methods using animal tracking on efficient result.","PeriodicalId":431894,"journal":{"name":"2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPCT.2016.7530223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
The proposed project performs motion detection and animal tracking based on background subtraction using multi threshold approach with mathematical morphology. Here the techniques frame differences; multi threshold based detection will be used. Along with this multi threshold, mathematical morphology also used which has an ability to attenuate color variations produced by background motions which will highlight moving objects. After the object foreground detection, the parameters like animal or human will be detected. Finally the simulated results will be shown. It will use approximate method with mathematical morphology approach rather than prior background subtraction methods using animal tracking on efficient result.