基于二维码和可逆可视水印的图像隐私保护方案

doi:10.11959/j.issn.1000-436x.2019220

摘要/Abstract

摘要：

针对图像在网络传输中的隐私信息泄露问题，提出了一种基于二维码和可逆可视水印的图像隐私保护方案。为了保护图像拍摄时间、拍摄地点和详细描述等隐私信息，首先将这类隐私信息加密后存储在云平台，并生成能够链接到加密隐私信息的统一资源定位符。该方案将统一资源定位符编码成二维码，并将该二维码作为可视水印可逆地嵌入图像中，实现对隐私信息的访问权限控制。在该方案中，使用视觉感知模型选择适合的水印嵌入参数，以平衡水印的可视性和载密图像的视觉质量。实验结果表明，该方案能够保证载密图像具有良好的视觉质量，同时不影响二维码的正确识别和解码。使用所提方案在保障图像传输质量的同时，也降低了隐私泄露的风险。

关键词: 二维码, 可逆信息隐藏, 可视水印, 隐私保护

Abstract:

With the privacy leakage problem of image delivery in networks,an image privacy preservation scheme based on QR code and reversible visible watermarking was proposed.In order to preserve the privacy information including shooting time,shooting location and detailed description,the encrypted privacy information was stored in cloud platforms and corresponding universal resource locator was generated firstly.Secondly,the universal resource locator was encoded as the QR code and it was embedded into the cover image using reversible visible watermarking.Therefore,the access control for privacy information could be achieved.The visual perceptual model was utilized to select adaptive watermark embedding parameters to balance watermark visibility and marked image quality.Experimental results demonstrate that the good visual quality of marked images can be obtained and the embedded QR code can be correctly decoded.The proposed scheme can guarantee marked image quality and reduce the risk of private information leakage.

Key words: QR code, reversible data hiding, visible watermarking, privacy preservation

中图分类号:

TP309.2

姚远志,王锋,严文博,俞能海. 基于二维码和可逆可视水印的图像隐私保护方案[J]. 通信学报, 2019, 40(11): 65-75.

Yuanzhi YAO,Feng WANG,Wenbo YAN,Nenghai YU. Image privacy preservation scheme based on QR code and reversible visible watermarking[J]. Journal on Communications, 2019, 40(11): 65-75.

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图像像素						嵌入参数α_i,j
图像像素	0.0	0.1	0.2	0.3	0.4	0.5	0.6	0.7	0.8	0.9	1.0
水印像素w_i,j =255	0	216	864	1 945	3 457	5 402	7 779	10 588	13 830	17 503	21 609
水印像素w_i,j =0	0	117	467	1 050	1 866	2 916	4 199	5 715	7 465	9 448	11 664

载体图像	Huang等算法		Mohammad等算法		Yao等算法		本文提出的算法
载体图像	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
Jetplane	18.445	0.793 1	23.201	0.943 6	27.401	0.954 3	26.750	0.976 5
Lena	17.146	0.755 0	22.493	0.941 2	25.746	0.944 7	27.903	0.974 5
Living room	17.482	0.795 7	21.500	0.935 2	25.892	0.945 6	29.692	0.975 1
Mandril	18.939	0.867 5	21.827	0.934 0	28.159	0.945 1	29.008	0.973 7
Peppers	17.325	0.746 2	21.810	0.940 3	26.791	0.944 3	28.755	0.973 7
Woman	17.400	0.800 8	21.471	0.935 4	26.069	0.938 1	28.269	0.972 5
均值	17.790	0.793 1	22.050	0.938 3	26.676	0.945 4	28.396	0.974 3
标准差	0.725	0.043 0	0.673	0.003 9	0.958	0.005 2	1.015	0.001 4

载体图像	Huang等算法		Mohammad等算法		Yao等算法		本文提出的算法
载体图像	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
Jetplane	11.736	0.554 3	17.990	0.786 8	21.734	0.818 8	18.102	0.857 6
Lena	11.062	0.435 1	17.099	0.773 9	20.132	0.795 1	20.456	0.853 9
Living room	11.460	0.560 5	16.787	0.774 6	20.770	0.808 4	21.069	0.858 8
Mandril	11.644	0.647 1	16.591	0.753 5	21.486	0.804 8	19.389	0.851 8
Peppers	11.657	0.471 1	16.411	0.774 3	21.510	0.783 5	21.034	0.853 9
Woman	12.103	0.539 9	16.711	0.766 9	21.597	0.783 8	20.686	0.854 6
均值	11.610	0.534 7	16.932	0.771 7	21.205	0.799 1	20.123	0.855 1
标准差	0.342	0.074 4	0.567	0.011 0	0.624	0.014 1	1.164	0.002 6

载体图像	均值	标准差
Jetplane	0.313	0.244
Lena	0.243	0.195
Living room	0.211	0.185
Mandril	0.304	0.254
Peppers	0.25	0.218
Woman	0.217	0.175

载体图像	均值	标准差
Jetplane	0.258	0.234
Lena	0.216	0.21
Living room	0.19	0.197
Mandril	0.224	0.221
Peppers	0.197	0.192
Woman	0.214	0.194