基于显著性检测的抗剪切攻击的图像数字水印方法

doi:10.13229/j.cnki.jdxbgxb.20240301

Abstract

Abstract:

To ensure that the embedded area of the watermark is preserved with a high probability during cropping， we propose an effective and anti-cropping attacked watermarking method. Firstly， we use a saliency detection network to select the embedding region； then we use a Transformer network to embed the transformed watermark into this region； to ensure the robustness of the watermark， a noise layer is used to attack the embedded image before extracting the watermark； finally， we use a fully convolutional network to extract watermark from the salient region. The experimental results show that the proposed method has higher robustness than compared methods under common nine attack methods. Our method can accurately extract the embedded watermark under saliency detection-based cropping attack.

Key words: computer application, image watermarking, saliency detection, cropping

CLC Number:

TP309

Rui HUANG,Ruo-xue YU,Wei FAN,Yan XING,Zi-yin CHEN. Anti⁃cropping digital image watermarking based on saliency detection[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(12): 4000-4009.

Figures/Tables 13

Fig.1

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Table 1

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Table 2

BER and SSIM of the attacked watermarked images obtained by different attack methods and inference time of different methods"

攻击方法	参数	DIWm		ReDMark		DAH-Net		本文方法
攻击方法	参数	BER	SSIM	BER	SSIM	BER	SSIM	BER	SSIM
椒盐噪声	0.4	0.367 7	0.314 4	0.135 8	0.690 2	0.226 1	0.378 8	0.004 5	0.973 7
	0.3	0.347 9	0.316 9	0.130 3	0.695 0	0.225 8	0.380 9	0.004 5	0.974 3
	0.2	0.314 0	0.325 6	0.127 4	0.697 1	0.224 8	0.385 4	0.004 5	0.975 3
剪切	0.6	0.194 4	0.596 6	0.163 6	0.682 7	0.085 0	0.856 6	0.003 7	0.982 4
	0.5	0.193 0	0.604 0	0.169 2	0.681 0	0.120 5	0.779 8	0.003 9	0.981 9
	0.4	0.191 6	0.612 7	0.173 3	0.679 9	0.152 5	0.706 7	0.003 9	0.980 8
裁剪替换	0.3	0.169 3	0.583 4	0.176 8	0.679 0	0.204 8	0.518 5	0.097 1	0.769 1
	0.2	0.176 2	0.524 3	0.179 1	0.678 5	0.227 7	0.457 5	0.125 9	0.736 4
	0.1	0.183 7	0.451 8	0.180 1	0.678 4	0.240 2	0.425 4	0.165 6	0.694 2
像素替换	0.4	0.139 9	0.804 7	0.138 0	0.690 4	0.102 2	0.725 6	0.021 9	0.949 2
	0.3	0.146 0	0.783 5	0.151 5	0.683 2	0.141 2	0.626 6	0.037 7	0.918 5
	0.2	0.142 0	0.748 4	0.171 3	0.679 7	0.183 5	0.533 5	0.065 0	0.868 8
高斯滤波	3	0.219 1	0.292 7	0.180 1	0.678 4	0.129 9	0.634 2	0.001 7	0.991 0
	2	0.201 0	0.304 9	0.180 1	0.678 4	0.084 3	0.744 3	0.009 8	0.963 9
	1	0.175 0	0.385 0	0.180 1	0.678 4	0.021 8	0.985 4	0.002 9	0.989 1
中值滤波	7	0.184 5	0.347 1	0.180 1	0.678 4	0.184 3	0.532 9	0.040 4	0.910 2
	5	0.167 3	0.391 3	0.180 1	0.678 4	0.113 6	0.669 4	0.025 4	0.926 2
	3	0.144 9	0.501 9	0.180 1	0.678 4	0.032 2	0.943 7	0.003 3	0.987 7
高斯噪声	0.2	0.348 6	0.318 9	0.180 1	0.678 4	0.224 5	0.380 9	0.004 5	0.975 3
	0.1	0.307 7	0.330 3	0.180 1	0.678 4	0.223 7	0.383 4	0.004 3	0.977 3
	0.05	0.255 0	0.357 8	0.180 1	0.678 4	0.222 3	0.386 8	0.003 7	0.980 3
JPEG压缩	50	0.099 5	0.857 3	0.134 9	0.687 8	0.224 3	0.446 3	0.173 1	0.687 3
	70	0.101 2	0.868 6	0.129 2	0.692 2	0.226 4	0.443 4	0.175 9	0.683 7
	90	0.091 0	0.932 8	0.126 4	0.697 7	0.230 0	0.438 9	0.085 7	0.835 6
缩放	1.2	0.132 8	0.602 1	0.170 8	0.677 9	0.027 5	0.948 9	0.002 5	0.990 3
	1.1	0.126 1	0.674 4	0.174 0	0.678 8	0.032 8	0.895 8	0.002 3	0.990 5
	0.9	0.135 3	0.593 7	0.179 3	0.678 5	0.033 7	0.891 2	0.002 3	0.990 9
时间/（张·s^-1）		0.29		0.06		0.35		0.15

Table 2

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Table 3

Table 4

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Table 5

Fig.8

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方法	嵌入水印的图像		提取的水印图像
方法	PSNR	SSIM	BER	SSIM
DIWm	32.13	0.96	0.124 7	0.817 6
ReDMark	25.03	0.77	0.125 4	0.696 2
DAH-Net	30.17	0.94	0.014 3	0.999 1
本文	31.50	0.92	0.002 0	0.992 4

方法	显著性裁剪攻击	BER	SSIM
DIWm	是	0.205 7	0.571 4
DIWm	否	0.124 7	0.817 6
ReDMark	是	0.170 4	0.681 5
ReDMark	否	0.125 4	0.696 2
DAH-Net	是	0.242 9	0.419 6
DAH-Net	否	0.014 3	0.999 1
本文	是	0.002 0	0.992 4
本文	否	0.000 3	0.998 2

实验	嵌入水印的图像		提取的水印图像
实验	PSNR	SSIM	BER	SSIM
未使用显著性网络	32.210 8	0.916 7	0.006 0	0.975 9
使用显著性网络	31.495 0	0.920 8	0.002 0	0.992 4

实验	嵌入水印的图像		提取的水印图像
实验	PSNR	SSIM	BER	SSIM
未使用水印冗余模块	31.670 3	0.918 4	0.032 0	0.912 9
使用水印冗余模块	31.495 0	0.920 8	0.002 0	0.992 4

Anti⁃cropping digital image watermarking based on saliency detection

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