{"title":"Image Moment Based Registration Scheme Utilizing Support Vector Machine","authors":"Jianzhen Wu","doi":"10.1109/IAS.2009.175","DOIUrl":null,"url":null,"abstract":"A novel image registration scheme is proposed in this paper. Six low order image moments are used as image global pattern features and are feed into support vector machine to estimate translation, rotation and scaling parameters. Simulation results show that the proposed registration scheme is accurate and robust to noise.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"54 50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fifth International Conference on Information Assurance and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.2009.175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A novel image registration scheme is proposed in this paper. Six low order image moments are used as image global pattern features and are feed into support vector machine to estimate translation, rotation and scaling parameters. Simulation results show that the proposed registration scheme is accurate and robust to noise.