载体独立的深度光照水印算法

doi:10.11959/j.issn.2096-109x.2022056

Abstract

Abstract:

With the development of multimedia techniques, the demand for copyright protection of digital products has also gradually risen.Digital watermarking is an effective means to protect the copyright of digital products.It is generally made by adding important identification information (i.e., digital watermark) to a digital carrier (e.g., text, image, etc.), so that the carrier carries the identification information but does not affect the normal use of the carrier.The common digital watermark embedding scheme is to embed the watermark information by modifying the carrier via specific algorithms.In the actual application scenarios, there are many images or objects to be protected (such as art paintings, etc.) that are not allowed to be modified.Based on this background, a new carrier-independent deep optical watermarking algorithm was proposed, which can realize watermark information embedding without modifying the original carrier and achieve the purpose of copyright protection.Specifically, a new watermark template expression scheme at the embedding end was proposed, which expressed the watermark information by visible light modulation.By analyzing the visual system of human eyes, a watermark template pattern based on alternating projection was proposed to embed the watermark information, which made the embedding process neither require modification of the original carrier nor affect the visual senses of human eyes.At the extraction end, a watermark extraction network based on residual connection was designed, and the captured watermarked images were fed into this network after perspective transformation to extract the watermark information.The experiments were conducted under various conditions and comparisons with three baseline algorithms were made.The experimental results show that the proposed algorithm generates watermarked images with less visual distortion and is robust to the ＆quot;projecting-shooting＆quot; process.The watermark extraction network has high accuracy in extracting watermark information at different distances, angles and illumination conditions, and has certain advantages over other general networks.

Key words: digital watermarking, human visual system, optical watermarking, deep neural network

CLC Number:

TP309.2

Hao CHEN, Feng WANG, Weiming ZHANG, Nenghai YU. Carrier-independent deep optical watermarking algorithm[J]. Chinese Journal of Network and Information Security, 2022, 8(4): 110-118.

Figures/Tables 10

References 34

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算法	MOS
DCT^[10]	2.63
WHT^[11]	2.87
Color-D^[13]	3.26
本文算法	4.28

光照强度/(cd/m²)	误码率
光照强度/(cd/m²)	DCT^[15]算法	WHT^[16]算法	Color-D^[17]算法	本文算法
50	23.53%	24.07%	19.53%	7.23%
100	19.78%	24.33%	17.69%	5.49%
150	14.25%	11.05%	12.42%	4.88%
200	14.38%	12.26%	9.07%	3.24%

距离/cm	误码率
距离/cm	DCT^[15]算法	WHT^[16]算法	Color-D^[17]算法	本文算法
30	8.29%	9.38%	7.26%	1.26%
40	12.16%	10.26%	10.33%	1.33%
50	23.05%	20.02%	15.01%	3.41%
60	22.09%	19.03%	20.21%	5.71%
70	27.65%	22.70%	23.52%	9.24%

角度	误码率
角度	DCT^[15]算法	WHT^[16]算法	Color-D^[17]算法	本文算法
左40°	23.75%	19.28%	19.35%	13.24%
左30°	20.09%	19.05%	17.26%	6.43%
左15°	14.27%	16.93%	11.28%	5.27%
右15°	13.73%	24.65%	14.38%	7.26%
右30°	18.22%	20.96%	15.33%	11.48%
右40°	30.35%	22.49%	23.26%	15.33%
上40°	22.44%	19.72%	20.20%	17.96%
上30°	24.96%	21.04%	12.33%	7.24%
上15°	16.28%	20.62%	9.03%	3.23%
下15°	17.96%	12.53%	11.24%	7.96%
下30°	20.35 %	22.01%	18.73%	12.48%
下40°	30.05%	26.28%	28.62%	17.39%

JPEG压缩质量因子	误码率
JPEG压缩质量因子	DCT^[15]算法	WHT^[16]算法	Color-D^[17]算法	本文算法
10	19.62%	15.30%	17.64%	4.07%
20	11.45%	9.22%	10.23%	3.69%
30	9.73%	9.09%	7.64%	4.24%

Carrier-independent deep optical watermarking algorithm

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Figures/Tables 10

References 34

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网络	误码率
GoogLeNet^[27]	3.56%
MobileNet^[28]	4.58%
LeNet^[29]	6.37%
PNASNet^[30]	4.93%
VGGNet^[31]	4.65%
EfficientNet^[32]	4.73%
DenseNet^[33]	4.54%
DPN^[34]	4.77%
本文网络	1.97%

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