{"title":"A Robust Digital Watermarking using Discrete Wavelet Transform in Chrominance Channel","authors":"K. Surachat","doi":"10.12720/JOACE.1.2.99-102","DOIUrl":null,"url":null,"abstract":"A wavelet-based digital watermarking scheme is presented in this paper. The watermark signal is embedded into HLn of LLn-1 transformed sub-band of original chrominance channel host image using coefficients scaling technique. In the extraction process, the average filter is applied to predict original dwt coefficients in HLn-1 subband. Then, the watermark logo is recovered by subtracting the coefficients predicted from the embedded coefficients, without original image needed. The obtained results show significant improvement in terms of quality and fidelity of extracted signal. Also, the improvements in terms of robustness by the proposed method work effectively against various common image-processing-based attacks especially against compression attacks. ","PeriodicalId":239044,"journal":{"name":"Journal of Automation and Control Engineering","volume":"49 16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Automation and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12720/JOACE.1.2.99-102","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
A wavelet-based digital watermarking scheme is presented in this paper. The watermark signal is embedded into HLn of LLn-1 transformed sub-band of original chrominance channel host image using coefficients scaling technique. In the extraction process, the average filter is applied to predict original dwt coefficients in HLn-1 subband. Then, the watermark logo is recovered by subtracting the coefficients predicted from the embedded coefficients, without original image needed. The obtained results show significant improvement in terms of quality and fidelity of extracted signal. Also, the improvements in terms of robustness by the proposed method work effectively against various common image-processing-based attacks especially against compression attacks.