Ola M. El Zein , Lamiaa M. El Bakrawy , Neveen I. Ghali
{"title":"一种基于模糊c均值聚类的鲁棒三维网格水印算法","authors":"Ola M. El Zein , Lamiaa M. El Bakrawy , Neveen I. Ghali","doi":"10.1016/j.fcij.2017.10.007","DOIUrl":null,"url":null,"abstract":"<div><p>A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 148-156"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.007","citationCount":"19","resultStr":"{\"title\":\"A robust 3D mesh watermarking algorithm utilizing fuzzy C-Means clustering\",\"authors\":\"Ola M. El Zein , Lamiaa M. El Bakrawy , Neveen I. Ghali\",\"doi\":\"10.1016/j.fcij.2017.10.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.</p></div>\",\"PeriodicalId\":100561,\"journal\":{\"name\":\"Future Computing and Informatics Journal\",\"volume\":\"2 2\",\"pages\":\"Pages 148-156\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.007\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Future Computing and Informatics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2314728817300132\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Computing and Informatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2314728817300132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A robust 3D mesh watermarking algorithm utilizing fuzzy C-Means clustering
A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.