H. Ozkaramali, A. Baradarani, H. Demirel, B. Ozmen, T. Çelik
{"title":"Moving Object Edge Detection and Segmentation using Multi-Wavelets","authors":"H. Ozkaramali, A. Baradarani, H. Demirel, B. Ozmen, T. Çelik","doi":"10.1109/SIU.2006.1659814","DOIUrl":null,"url":null,"abstract":"Moving object edge detection and segmentation method is presented with utilizing multi-wavelets. The subsequent segmentation of moving objects is achieved by binary morphological operations. The proposed multi-wavelet based method is compared with the methods based on scalar wavelets using both single and double change detection techniques. The simulation results indicate that multi-wavelets with repeated row pre-processing employing double change detection method outperform scalar wavelet-based methods in the number of detected moving edges and better preserve the moving edges. As a result the quality of moving object segmentation has been improved over the scalar methods","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE 14th Signal Processing and Communications Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2006.1659814","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Moving object edge detection and segmentation method is presented with utilizing multi-wavelets. The subsequent segmentation of moving objects is achieved by binary morphological operations. The proposed multi-wavelet based method is compared with the methods based on scalar wavelets using both single and double change detection techniques. The simulation results indicate that multi-wavelets with repeated row pre-processing employing double change detection method outperform scalar wavelet-based methods in the number of detected moving edges and better preserve the moving edges. As a result the quality of moving object segmentation has been improved over the scalar methods