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Titlebook: Digital Forensics and Watermarking; 15th International W Yun Qing Shi,Hyoung Joong Kim,Feng Liu Conference proceedings 2017 Springer Intern

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樓主: Hayes
21#
發(fā)表于 2025-3-25 05:44:40 | 只看該作者
P. Savithri,R. Perumal,R. Nagarajanerminals should not be ignored as well. In this paper, we investigate the color mixture model of a well-known psychophysical phenomenon: “persistence of vision”, and propose a new display technology which presents secret and cheating information at the same time. Unauthorized viewers only see the ch
22#
發(fā)表于 2025-3-25 10:36:40 | 只看該作者
V. Balasubramanian,J. K. Ladha,G. L. Denning design. However, most of the previous RG-based threshold VSS still suffer from low visual quality or worse reconstructed secrets when more shares are stacked. In this paper, a new RG-based VSS with improved visual quality is proposed. The random bits are utilized to improve the visual quality as we
23#
發(fā)表于 2025-3-25 12:59:00 | 只看該作者
Resource Management and Transport Layer information. In this paper, we propose a (.,?.)-HVCS using complementary cover images. Before the halftone processing of the cover images by error diffusion, secret information pixels (SIPs) are prefixed based on the underlying (.,?.)-VCS. In the halftone processing, several pairs of complementary
24#
發(fā)表于 2025-3-25 17:49:47 | 只看該作者
25#
發(fā)表于 2025-3-25 23:45:20 | 只看該作者
26#
發(fā)表于 2025-3-26 00:43:37 | 只看該作者
978-3-319-53464-0Springer International Publishing AG 2017
27#
發(fā)表于 2025-3-26 07:50:14 | 只看該作者
Digital Forensics and Watermarking978-3-319-53465-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
28#
發(fā)表于 2025-3-26 08:59:42 | 只看該作者
Using Benford’s Law Divergence and Neural Networks for Classification and Source Identification of B Benford’s law are used as input features for a Neural Network for the classification and source identification of biometric images. Experimental analysis shows that the classification and identification of the source of the biometric images can achieve good accuracies between the range of 90.02% and 100%.
29#
發(fā)表于 2025-3-26 13:37:30 | 只看該作者
30#
發(fā)表于 2025-3-26 19:35:21 | 只看該作者
Random Grids-Based Threshold Visual Secret Sharing with Improved Visual Quality stacked. In this paper, a new RG-based VSS with improved visual quality is proposed. The random bits are utilized to improve the visual quality as well as to decrease the darkness of the reconstructed secret image in the proposed scheme. Experimental results and analyses show the effectiveness of the proposed scheme.
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