Abstract
In recent years, there has been an increasing concern regarding the security and copyright issues associated with images. Unscrupulous individuals exploit electronic images through theft and manipulation, subsequently disseminating them widely, thereby posing significant threats to image copyright ownership and reliability. To address potential screen-shooting attacks on images, this paper proposes a robust watermarking algorithm based on entropy-weighted Harris corner detection and adaptive embedding radius. Firstly, this algorithm uses entropy as the weighted coefficient of Harris corner response values to extract feature points with rich texture features and high robustness. Then, the SIFT algorithm is used to assign orientations to feature points and construct and filter out non-overlapping feature regions. Next, the embedding radius of the watermark is adaptively selected based on the average gray value of the image feature region, and the watermark is embedded into the DFT coefficients of the image feature region. Finally, after completing the watermark embedding in all feature regions, the watermarked image is obtained. In the watermark extraction stage, the captured image is first geometrically distorted and then processed with a Gaussian function before extracting the watermark information from the image. Experimental results show that this algorithm has strong robustness against screen-shooting attacks and common image attacks, while maintaining high transparency.
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References
Singh, P.O., Singh, K.A., Zhou, H.: Multimodal fusion-based image hiding algorithm for secure healthcare system. In: IEEE Intelligent Systems (2022)
Singh, P.O., Singh, N.K., Baranwal, N.: Hidemarks: hiding multiple marks for robust medical data sharing using IWT-LSB. In: Multimedia Tools and Applications, pp. 1–19 (2023)
Mahto, K.D., Singh, K.A., Singh, N.K: Robust copyright protection technique with high-embedding capacity for color images. In: ACM Transactions on Multimedia Computing, Communications and Applications (2023)
Schaber, P., Kopf, S., Wetzel, S.: Cammark: analyzing, modeling, and simulating artifacts in camcorder copies. In: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), pp. 1–23 (2015)
Katayama, A.: New high-speed frame detection method: side trace algorithm (STA) for i-appli on cellular phones to detect watermarks. In: Proceedings of the 3rd International Conference on Mobile and Ubiquitous Multimedia (2004)
Pramila, A., Keskinarkaus, A., Seppänen, T.: Toward an interactive poster using digital watermarking and a mobile phone camera. Signal, Image Video Process. 6(2), 211–222 (2012)
Pramila, A., Keskinarkaus, A., Takala, V.: Extracting watermarks from printouts captured with wide angles using computational photography. In: Multimedia Tools and Applications, vol. 76 (2016)
Pramila, A., Keskinarkaus, A., Seppänen, T.: Increasing the capturing angle in print-cam robust watermarking. In: Journal of Systems and Software, vol. 135, pp. 205–215 (2018)
Gourrame, K., Douzi, H., Harba, R.: Robust print-cam image watermarking in Fourier domain. In: International Conference on Image and Signal Processing. Springer, Cham, pp. 356–365 (2016)
Gourrame, K., Douzi, H., Harba, R., Riad, R., Ros, F., Amar, M., Elhajji, M.: A zero-bit Fourier image watermarking for print-cam process. Multimed. Tools Appl 78, 2621–2638 (2019)
Wang, Y., Wang, X.: Print-cam robust image watermarking based on hybrid domain. In: 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP), pp. 1911–1915 (2022)
Wang, X.: Research on digital watermarking algorithm oriented to screen capture process for remote sensing image. In: Nanjing Normal University (2018)
Fang, H., Zhang, W., Zhou, H.: Screen-shooting resilient watermarking. IEEE Trans. Inf. Forens. Secur. 14(6), 1403–1418 (2018)
Fang, H., Zhang, W., Ma, Z.: A camera shooting resilient watermarking scheme for underpainting documents. IEEE Trans. Circuits Syst. Video Technol. 30(11), 4075–4089 (2019)
Chen, W., Ren, N., Zhu, C.: Screen-cam robust image watermarking with feature-based synchronization. Appl. Sci. 10, 7494 (2020). https://doi.org/10.3390/app10217494
Bai, Y., Li, L., Zhang, S.: Fast frequency domain screen-shooting watermarking algorithm based on orb feature points. Mathematics 11, 1730 (2023). https://doi.org/10.3390/math11071730
Dong, L., Chen, J., Peng, C.: Watermark-preserving keypoint enhancement for screen-shooting resilient watermarking. In: IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6. IEEE (2022) https://doi.org/10.1109/ICME52920.2022.9859950
Deng, B., Li, S., Qian, Z.: An svd-based screen-shooting resilient watermarking scheme. In: Multimedia Tools and Applications, pp. 1–15 (2022). https://doi.org/10.1007/s11042-022-12738-x
Li, L., Bai, R., Zhang, S.: Screen-shooting resilient watermarking scheme via learned invariant keypoints and qt. Sensors 21(19), 6554 (2021)
Fang, H., Chen, D., Huang, Q.: Deep template-based watermarking. IEEE Trans. Multimed. 31, 1436–1451 (2020)
Cao, F., Wang, T., Guo, D.: Screen-shooting resistant image watermarking based on lightweight neural network in frequency domain. In: Journal of Visual Communication and Image Representation, p. 103837 (2023)
Mikolajczyk, K., Schmid, C.: Indexing based on scale invariant interest points. In: Proceedings 8th IEEE International Conference on Computer Vision, pp. 525–531. ICCV (2001)
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of the 7th IEEE International Conference on Computer Vision, vol. 2 (1999)
Ying, Q., Lin, J., Qian, Z.: Robust digital watermarking for color images in combined dft and dt-cwt domains. Math. Biosci. Eng. 16, 4788–4801 (2019)
Rabia, R., Ros, F., Harba, R.: Enhancement of Fourier image watermarking robustness. J. Control Eng. Appl. Informat. 19, 25–33 (2017)
Southern California, U.: The USC-SIPI image database, signal and image processing institute. https://sipi.usc.edu/database
Gu, S., Han, J., Sun, X.: Robust watermarking of screen-photography based on jnd. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), vol. 71 (2022). https://doi.org/10.32604/cmc.2022.023955
Funding
This work is supported by the National Natural Science Foundation of China (Grant Nos. 61802111, 61872125), the Science and Technology Project of Henan Province (Grant Nos. 232102210109, 212102210094), and Pre-research Project of SongShan Laboratory (No. YYJC012022011).
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ZG Software, Visualization, Data duration, Funding acquisition. XZ Conceptualization, Writing-reviewing and Editing. YS Methodology, Writing-original draft preparation, Writing-reviewing and Editing, Supervision. XC Investigation, Visualization, Validation. All authors have read and agreed to the published version of the manuscript.
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Gan, Z., Zheng, X., Song, Y. et al. Screen-shooting watermarking algorithm based on Harris-SIFT feature regions. SIViP 18, 4647–4660 (2024). https://doi.org/10.1007/s11760-024-03102-7
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DOI: https://doi.org/10.1007/s11760-024-03102-7