{"title":"Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation","authors":"P.J.R. Shalem Raju, K.V.D. Kiran, Pokkuluri Kiran Sree","doi":"10.1504/ijcvr.2023.134319","DOIUrl":null,"url":null,"abstract":"The image watermarking topologies afford a promising solution in digital media copyright protection. However, it is essential to take into account the robustness of watermarking methods. Therefore, in this paper, a digital image watermarking technique based on finite ridgelet transform (FRT), discrete wavelet transform (DWT), and Hessenberg decomposition (HD) is proposed. The FRT and HD methods are hybridised with DWT to enhance the embedding capacity. Likewise, the embedding strength factor is also optimised through a flamingo search algorithm (FSA). After embedding the extraction process is carried out with deep belief neural (DBN) network. The experiments are conducted on four kinds of host images like Lena, house, baboon, and Barbara in MATLAB platform. The results are compared with different models in terms of peak signal to noise ratio (PSNR), normalisation coefficient (NC), and structural similarity index measure (SSIM) under various geometric attacks.","PeriodicalId":38525,"journal":{"name":"International Journal of Computational Vision and Robotics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Vision and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijcvr.2023.134319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
The image watermarking topologies afford a promising solution in digital media copyright protection. However, it is essential to take into account the robustness of watermarking methods. Therefore, in this paper, a digital image watermarking technique based on finite ridgelet transform (FRT), discrete wavelet transform (DWT), and Hessenberg decomposition (HD) is proposed. The FRT and HD methods are hybridised with DWT to enhance the embedding capacity. Likewise, the embedding strength factor is also optimised through a flamingo search algorithm (FSA). After embedding the extraction process is carried out with deep belief neural (DBN) network. The experiments are conducted on four kinds of host images like Lena, house, baboon, and Barbara in MATLAB platform. The results are compared with different models in terms of peak signal to noise ratio (PSNR), normalisation coefficient (NC), and structural similarity index measure (SSIM) under various geometric attacks.