{"title":"基于盲源分离的小波域嵌入鲁棒数字图像水印","authors":"Sangeeta Jadhav, A. Bhalchandra","doi":"10.1109/ICCIS.2010.5518562","DOIUrl":null,"url":null,"abstract":"In a digital watermarking scheme, it is not convenient to carry the original image all the time in order to detect the owner's signature from the watermarked image. Moreover, for those applications that require different watermarks for different copies, it is preferred to utilize some kind of watermark-independent algorithm for extraction process i.e. dewatermarking. Watermark embedding is performed in the blue channel, as it is less sensitive to human visual system. This paper proposes a new color image watermarking method, which adopts Blind Source Separation (BSS) technique for watermark extraction. Single level Discrete Wavelet Transform (DWT) is used for embedding. The novelty of our scheme lies in determining the mixing matrix for BSS model during embedding. The determination of mixing matrix using Quasi-Newton's (BFGS) technique is based on texture analysis which uses energy content of the image. This makes our method image adaptive to embed the watermark into original image so as not to bring about a perceptible change in the marked image. BSS based on Joint diagonalization of the time delayed covariance matrices algorithm is used for the extraction of watermark. The proposed method, undergoing different experiments, has shown its robustness against many attacks including rotation, low pass filtering, salt n pepper noise addition and compression. The robustness evaluation is also carried out with respect to the spatial domain embedding.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Blind Source Separation based robust digital image watermarking using wavelet domain embedding\",\"authors\":\"Sangeeta Jadhav, A. Bhalchandra\",\"doi\":\"10.1109/ICCIS.2010.5518562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a digital watermarking scheme, it is not convenient to carry the original image all the time in order to detect the owner's signature from the watermarked image. Moreover, for those applications that require different watermarks for different copies, it is preferred to utilize some kind of watermark-independent algorithm for extraction process i.e. dewatermarking. Watermark embedding is performed in the blue channel, as it is less sensitive to human visual system. This paper proposes a new color image watermarking method, which adopts Blind Source Separation (BSS) technique for watermark extraction. Single level Discrete Wavelet Transform (DWT) is used for embedding. The novelty of our scheme lies in determining the mixing matrix for BSS model during embedding. The determination of mixing matrix using Quasi-Newton's (BFGS) technique is based on texture analysis which uses energy content of the image. This makes our method image adaptive to embed the watermark into original image so as not to bring about a perceptible change in the marked image. BSS based on Joint diagonalization of the time delayed covariance matrices algorithm is used for the extraction of watermark. The proposed method, undergoing different experiments, has shown its robustness against many attacks including rotation, low pass filtering, salt n pepper noise addition and compression. The robustness evaluation is also carried out with respect to the spatial domain embedding.\",\"PeriodicalId\":445473,\"journal\":{\"name\":\"2010 IEEE Conference on Cybernetics and Intelligent Systems\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Conference on Cybernetics and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2010.5518562\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2010.5518562","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind Source Separation based robust digital image watermarking using wavelet domain embedding
In a digital watermarking scheme, it is not convenient to carry the original image all the time in order to detect the owner's signature from the watermarked image. Moreover, for those applications that require different watermarks for different copies, it is preferred to utilize some kind of watermark-independent algorithm for extraction process i.e. dewatermarking. Watermark embedding is performed in the blue channel, as it is less sensitive to human visual system. This paper proposes a new color image watermarking method, which adopts Blind Source Separation (BSS) technique for watermark extraction. Single level Discrete Wavelet Transform (DWT) is used for embedding. The novelty of our scheme lies in determining the mixing matrix for BSS model during embedding. The determination of mixing matrix using Quasi-Newton's (BFGS) technique is based on texture analysis which uses energy content of the image. This makes our method image adaptive to embed the watermark into original image so as not to bring about a perceptible change in the marked image. BSS based on Joint diagonalization of the time delayed covariance matrices algorithm is used for the extraction of watermark. The proposed method, undergoing different experiments, has shown its robustness against many attacks including rotation, low pass filtering, salt n pepper noise addition and compression. The robustness evaluation is also carried out with respect to the spatial domain embedding.