{"title":"A public key watermarking based on hyper-chaotic cellular neural network","authors":"Li-zong Li, Tieniu Gao, Q. Gu, Qunting Yang","doi":"10.1109/ICWAPR.2010.5576461","DOIUrl":null,"url":null,"abstract":"In this paper, a new watermarking using cell neural network with hyper-chaotic cellular neural network (HCCNN) is proposed. In the scheme, the pixel values of the image are used to the input of the HCCNN. The outputs of the HCCNN are encrypted by the public key system, and then are embedded into the LSBs of the original image. The receiver can verify the suspected image with the signer's public key. Simulations show that the scheme can detect if the key is incorrect, if the image is tampered in its pixel values, and moreover, can detect and locate the position of any slightly tampered parts for a suspected image.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2010.5576461","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
In this paper, a new watermarking using cell neural network with hyper-chaotic cellular neural network (HCCNN) is proposed. In the scheme, the pixel values of the image are used to the input of the HCCNN. The outputs of the HCCNN are encrypted by the public key system, and then are embedded into the LSBs of the original image. The receiver can verify the suspected image with the signer's public key. Simulations show that the scheme can detect if the key is incorrect, if the image is tampered in its pixel values, and moreover, can detect and locate the position of any slightly tampered parts for a suspected image.