ew 18: e39

Research Article

Text Steganography in Statistically Clustered Iris Image

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  • @ARTICLE{10.4108/eai.18-11-2020.167100,
        author={Irtefaa A. Neamah and Hind Rustum Mohammed},
        title={Text Steganography in Statistically Clustered Iris Image},
        journal={EAI Endorsed Transactions on Energy Web: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={EW},
        year={2020},
        month={11},
        keywords={Steganography, PNSR, MSE, Clustered Image, Iris Image},
        doi={10.4108/eai.18-11-2020.167100}
    }
    
  • Irtefaa A. Neamah
    Hind Rustum Mohammed
    Year: 2020
    Text Steganography in Statistically Clustered Iris Image
    EW
    EAI
    DOI: 10.4108/eai.18-11-2020.167100
Irtefaa A. Neamah1,*, Hind Rustum Mohammed2
  • 1: Assistant Professor, Department of Mathematics, Faculty of Computer Science and Mathematics, University of Kufa, Iraq
  • 2: Professor, Department of Computer Science, Faculty of Computer Science and Mathematics, University of Kufa, Iraq
*Contact email: irtefaa.radhi@uokufa.edu.iq

Abstract

The hiding text within the iris to increase the data protection method is discussed in this work. It is impossible to distinguish between the iris image before and after concealment, and the difference between the two images only after using statistical measures such as PSNR and MSR to compare them. The proposed database consists of 500 images with different formats (tif, gif, png, jpg, .bmp) selected for analysis. The proposed method is shown with more accurate results, stronger image encoding, and high-efficiency text protection using performance evaluation factors to assess business standards. The success of hiding high-text ratios proved successful. Experimental results were shown based on a statistical strategy, and that the text was converted into two random variables, X and Y, which were distributed to Asia. Then, the random variables' data were included in the iris segment, cut-off, and iris' clustered image. It appears that the use of our proposed scheme can include sufficient data in the image of the iris that maintains the accuracy of the identification.