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Improving Quality of Multiple Secret Shares Using GSNL Filter in Visual Cryptography


Affiliations
1 Department of Computer Science and Technology, Karunya University, Coimbatore, India
     

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In this paper, (Embedded Extended Visual Cryptography Scheme (EEVCS) is utilized to hide multiple secret images into two or more meaningful cover images which are called share images with no pixel expansion. The manifold secret images are concatenated and embed in the respective number of cover images. People who congregate the multiple share images can acquire either the separated secret images or the concatenated secret images by stacking them without any complex computation. The visual quality of the stacked share is improved using general sliding neighborhood filter (GSNL FILTER) that exploits the functionalities of sliding window protocol, pixel padding, sorting and filtering. Visual quality factors like PSNR (Peak Signal-to-Noise Ratio), UQI (Universal Quality Index), EME (Enhancement Measure of Entropy), SSIM (Structural Similarity of Image Measure), and Mean SSIM are determined and compared with the existing values to appraise the enhanced factors.

Keywords

Enhancement Measure of Entropy (EME), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity of Image Measure (SSIM), Universal Quality Index (UQI).
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  • Improving Quality of Multiple Secret Shares Using GSNL Filter in Visual Cryptography

Abstract Views: 215  |  PDF Views: 2

Authors

Linda Mol Ouseph
Department of Computer Science and Technology, Karunya University, Coimbatore, India
Iwin Thanakumar Joseph
Department of Computer Science and Technology, Karunya University, Coimbatore, India

Abstract


In this paper, (Embedded Extended Visual Cryptography Scheme (EEVCS) is utilized to hide multiple secret images into two or more meaningful cover images which are called share images with no pixel expansion. The manifold secret images are concatenated and embed in the respective number of cover images. People who congregate the multiple share images can acquire either the separated secret images or the concatenated secret images by stacking them without any complex computation. The visual quality of the stacked share is improved using general sliding neighborhood filter (GSNL FILTER) that exploits the functionalities of sliding window protocol, pixel padding, sorting and filtering. Visual quality factors like PSNR (Peak Signal-to-Noise Ratio), UQI (Universal Quality Index), EME (Enhancement Measure of Entropy), SSIM (Structural Similarity of Image Measure), and Mean SSIM are determined and compared with the existing values to appraise the enhanced factors.

Keywords


Enhancement Measure of Entropy (EME), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity of Image Measure (SSIM), Universal Quality Index (UQI).