{"title":"Blind Watermarking in Contourlet Domain with Improved Detection","authors":"M. Jayalakshmi, S. Merchant, U. Desai","doi":"10.1109/IIH-MSP.2006.65","DOIUrl":null,"url":null,"abstract":"This paper presents a novel method of blind image watermarking in contourlet domain. We have used spread spectrum technique for additive watermark embedding. A correlation detector is used to detect the embedded pseudorandom sequence. The binary logo thus retrieved proves authenticity of the image. The similarity of the retrieved binary logo with the original embedded logo is veriJied using correlation technique. Post processing of the retrieved logo gives better visual effects, further aiding threshold selection for detection. We have verijied the robustness of the proposed method against dzrerent attacks including StirMark attack. The proposed method is compared with a wavelet based blind technique and the results prove that contourlet based technique gives better robustness, under similar embedding conditions.","PeriodicalId":272579,"journal":{"name":"2006 International Conference on Intelligent Information Hiding and Multimedia","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Intelligent Information Hiding and Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIH-MSP.2006.65","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
This paper presents a novel method of blind image watermarking in contourlet domain. We have used spread spectrum technique for additive watermark embedding. A correlation detector is used to detect the embedded pseudorandom sequence. The binary logo thus retrieved proves authenticity of the image. The similarity of the retrieved binary logo with the original embedded logo is veriJied using correlation technique. Post processing of the retrieved logo gives better visual effects, further aiding threshold selection for detection. We have verijied the robustness of the proposed method against dzrerent attacks including StirMark attack. The proposed method is compared with a wavelet based blind technique and the results prove that contourlet based technique gives better robustness, under similar embedding conditions.