H. Ozkaramali, A. Baradarani, H. Demirel, B. Ozmen, T. Çelik
{"title":"基于多小波的运动目标边缘检测与分割","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":"{\"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}","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}
Moving Object Edge Detection and Segmentation using Multi-Wavelets
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