Traditional guidance mechanism based deep robust watermarking
With the development of network and multimedia technology, multimedia data has gradually become a key source of information for people, making digital media the primary battlefield for copyright protection and anti-counterfeit traceability.Digital watermarking techniques have been widely studied and...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2023-04-01
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| Series: | 网络与信息安全学报 |
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| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2023031 |
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| _version_ | 1841529687523721216 |
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| author | Xuejing GUO Yixiang FANG Yi ZHAO Tianzhu ZHANG Wenchao ZENG Junxiang WANG |
| author_facet | Xuejing GUO Yixiang FANG Yi ZHAO Tianzhu ZHANG Wenchao ZENG Junxiang WANG |
| author_sort | Xuejing GUO |
| collection | DOAJ |
| description | With the development of network and multimedia technology, multimedia data has gradually become a key source of information for people, making digital media the primary battlefield for copyright protection and anti-counterfeit traceability.Digital watermarking techniques have been widely studied and recognized as important tools for copyright protection.However, the robustness of conventional digital watermarking methods is limited as sensitive digital media can easily be affected by noise and external interference during transmission.Then the existing powerful digital watermarking technology’s comprehensive resistance to all forms of attacks must be enhanced.Moreover, the conventional robust digital watermarking algorithm’s generalizability across a variety of image types is limited due to its embedding method.Deep learning has been widely used in the development of robust digital watermarking systems due to its self-learning abilities.However, current initialization techniques based on deep neural networks rely on random parameters and features, resulting in low-quality model generation, lengthy training times, and potential convergence issues.To address these challenges, a deep robust digital watermarking algorithm based on a traditional bootstrapping mechanism was proposed.It combined the benefits of both traditional digital watermarking techniques and deep neural networks, taking into account their learning abilities and robust characteristics.The algorithm used the classic robust digital watermarking algorithm to make watermarked photos, and the constructed feature guaranteed the resilience of traditional watermarked images.The final dense image was produced by fusing the conventionally watermarked image with the deep network using the U-Net structure.The testing results demonstrate that the technique can increase the stego image’s resistance to various attacks and provide superior visual quality compared to the conventional algorithm. |
| format | Article |
| id | doaj-art-3b23934519924828a890bcdcb7844d36 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2023-04-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-3b23934519924828a890bcdcb7844d362025-01-15T03:16:24ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2023-04-01917518359576657Traditional guidance mechanism based deep robust watermarkingXuejing GUOYixiang FANGYi ZHAOTianzhu ZHANGWenchao ZENGJunxiang WANGWith the development of network and multimedia technology, multimedia data has gradually become a key source of information for people, making digital media the primary battlefield for copyright protection and anti-counterfeit traceability.Digital watermarking techniques have been widely studied and recognized as important tools for copyright protection.However, the robustness of conventional digital watermarking methods is limited as sensitive digital media can easily be affected by noise and external interference during transmission.Then the existing powerful digital watermarking technology’s comprehensive resistance to all forms of attacks must be enhanced.Moreover, the conventional robust digital watermarking algorithm’s generalizability across a variety of image types is limited due to its embedding method.Deep learning has been widely used in the development of robust digital watermarking systems due to its self-learning abilities.However, current initialization techniques based on deep neural networks rely on random parameters and features, resulting in low-quality model generation, lengthy training times, and potential convergence issues.To address these challenges, a deep robust digital watermarking algorithm based on a traditional bootstrapping mechanism was proposed.It combined the benefits of both traditional digital watermarking techniques and deep neural networks, taking into account their learning abilities and robust characteristics.The algorithm used the classic robust digital watermarking algorithm to make watermarked photos, and the constructed feature guaranteed the resilience of traditional watermarked images.The final dense image was produced by fusing the conventionally watermarked image with the deep network using the U-Net structure.The testing results demonstrate that the technique can increase the stego image’s resistance to various attacks and provide superior visual quality compared to the conventional algorithm.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2023031watermarking technologydeep networkrobust watermarkingU-Net |
| spellingShingle | Xuejing GUO Yixiang FANG Yi ZHAO Tianzhu ZHANG Wenchao ZENG Junxiang WANG Traditional guidance mechanism based deep robust watermarking 网络与信息安全学报 watermarking technology deep network robust watermarking U-Net |
| title | Traditional guidance mechanism based deep robust watermarking |
| title_full | Traditional guidance mechanism based deep robust watermarking |
| title_fullStr | Traditional guidance mechanism based deep robust watermarking |
| title_full_unstemmed | Traditional guidance mechanism based deep robust watermarking |
| title_short | Traditional guidance mechanism based deep robust watermarking |
| title_sort | traditional guidance mechanism based deep robust watermarking |
| topic | watermarking technology deep network robust watermarking U-Net |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2023031 |
| work_keys_str_mv | AT xuejingguo traditionalguidancemechanismbaseddeeprobustwatermarking AT yixiangfang traditionalguidancemechanismbaseddeeprobustwatermarking AT yizhao traditionalguidancemechanismbaseddeeprobustwatermarking AT tianzhuzhang traditionalguidancemechanismbaseddeeprobustwatermarking AT wenchaozeng traditionalguidancemechanismbaseddeeprobustwatermarking AT junxiangwang traditionalguidancemechanismbaseddeeprobustwatermarking |