تشخیص و بازیابی تصاویر تحت حملات با نرخ دستکاری بالا
محورهای موضوعی : مهندسی برق و کامپیوترفرانک توحیدی 1 , محمدرضا هوشمنداصل 2
1 - دانشگاه یزد
2 - دانشگاه محقق اردبیلی
کلید واژه: نهان‌نگاری, تشخیص دستکاری, بازیابی داده, بازیابی تصویر,
چکیده مقاله :
در سال‌های اخیر با رشد روزافزون فناوری‌های دیجیتال، نسخه‌برداری عکس‌های دیجیتال و حتی تغییر آنها بدون افت کیفیت و با هزینه اندک امکانپذیر شده است. نهان‌نگاری، یکی از روش‌های موفق تشخیص دستکاری و حتی بازیابی داده‌های اصلی می‌باشد؛ ولی هنوز مشکلات زیادی برای ارائه یک نهان‌نگار مناسب که قادر به تشخیص و بازیابی هر نوع دستکاری باشد، وجود دارد. این مشکلات خصوصاً در مواردی که حملات خاص دستکاری با نرخ بالا صورت می‌گیرد حادتر خواهد بود. در این مقاله یک روش نهان‌نگار معرفی شده که نه‌تنها قادر به تشخیص هر گونه دستکاری است، بلکه در نرخ‌های بالای دستکاری نیز می‌تواند داده‌های اصلی را با کیفیت بالا بازیابی کند. در این مقاله برای تشخیص دستکاری از تجزیه به مؤلفه‌های تکین (SVD) استفاده می‌شود. همچنین نهان‌نگار برای بازیابی داده‌های از دست رفته از روش مبتنی بر OIBTC استفاده می‌کند. این مقاله روشی کارا برای افزایش حساسیت تشخیص و در عین حال افزایش مقاومت نهان‌نگار برای بازیابی ارائه می‌دهد. نتایج به‌دست‌آمده برتری روش پیشنهادشده را نسبت به روش‌های اخیر ثابت می‌کنند.
In recent years, illegally copying digital images and even manipulating them, without great loss of quality and at a low cost has been made possible. Watermarking has recently been developed as one of the methods to detect that tampering has occurred and even enable some recovery of the original images. However, there are still many issues to resolve in providing an effective watermark that can detect and recover a wide range of manipulations. Furthermore, the accuracy of detecting and the capability of the recovery of the original images by existing methods are still not at an acceptable level. These problems are more critical when certain high-rate manipulation attacks occur. In this paper, a watermarking method will be introduced that not only is able to detect any tampering, but also can successfully recover the original images in high quality, even at high tampering rates. In this method, Singular Value Decomposition (SVD) is used to detect tampering and Optimal Iterative Block Truncation Coding (OIBTC) has also been applied to recover lost data. This paper proposes a powerful way to increase detection sensitivity while increasing watermark resistance for the effective recovery of corrupted images. The results prove the superiority of the proposed method over current methods.92% of tasks are executed successfully in the edge environment.
[1] L. Rakhmawati, W. Wirawan, and S. Suwadi, "A recent survey of self-embedding fragile watermarking scheme for image authentication with recovery capability," EURASIP J. on Image and Video Processing, vol. 2019, Article ID: 61, 2019.
[2] B. B. Haghighi, A. H. Taherinia, and A. H. Mohajerzadeh, "TRLG: fragile blind quad watermarking for image tamper detection and recovery by providing compact digests with optimized quality using LWT and GA," Information Sciences, vol. 486, pp. 204-230, Jun. 2019.
[3] C. Qin, C. Chang, and P. Chen, "Self-embedding fragile watermarking with restoration capability based on adaptive bit allocation mechanism," Signal Processing, vol. 92, no. 4, pp. 1137-1150, Apr. 2012.
[4] Y. Huo, H. He, and F. Chen, "Alterable-capacity fragile watermarking scheme with restoration capability," Optics Communications, vol. 285, no. 7, pp. 1759-1766, Apr. 2012.
[5] C. Qin, P. Ji, C. C. Chang, J. Dong, and X. Sun, "Non-uniform watermark sharing based on optimal iterative BTC for image tampering recovery," IEEE MultiMedia, vol. 25, no. 3, pp. 36-48, Jul.-Sept. 2018.
[6] M. Hamid and C. Wang, "Adaptive image self-recovery based on feature extraction in the DCT domain," IEEE Access, vol. 6, pp. 67156-67165, 2018.
[7] B. B. Haghighi, A. H. Taherinia, and A. Harati, "TRLH: fragile and blind dual watermarking for image tamper detection and self-recovery based on lifting wavelet transform and halftoning technique," J. of Visual Communication and Image Representation, vol. 50, pp. 49-64, Jan. 2018.
[8] K. Sreenivas and V. Kamakshiprasad, "Improved image tamper localisation using chaotic maps and self-recovery," J. of Visual Communication and Image Representation, vol. 49, pp. 164-176, Nov. 2017.
[9] C. S. Hsu and S. F. Tu, "Image tamper detection and recovery using adaptive embedding rules," Measurement, vol. 88, pp. 287-296, Jun. 2016.
[10] A. Azeroual and K. Afdel, "Real-time image tamper localization based on fragile watermarking and Faber-Schauder wavelet," AEU-International J. of Electronics and Communications, vol. 79, pp. 207-218, Sept. 2017.
[11] R. O. Preda, "Semi-fragile watermarking for image authentication with sensitive tamper localization in the wavelet domain," Measurement, vol. 46, no. 1, pp. 367-373, Jan. 2013.
[12] C. Qin and X. Zhang, "Effective reversible data hiding in encrypted image with privacy protection for image content," J. of Visual Communication and Image Representation, vol. 31, pp. 154-164, Aug. 2015.
[13] M. A. Wahed and H. Nyeem, "High capacity reversible data hiding with interpolation and adaptive embedding," PloS One, vol. 14, no. 3, Article ID: e0212093, 2019.
[14] X. T. Wang, C. C. Chang, T. S. Nguyen, and M. C. Li, "Reversible data hiding for high quality images exploiting interpolation and direction order mechanism," Digital Signal Processing, vol. 23, no. 2, pp. 569-577, Mar. 2013.
[15] A. Malik, G. Sikka, and H. Kumar Verma, "An image interpolation based reversible data hiding scheme using pixel value adjusting feature," Multimedia Tools and Applications, vol. 76, no. 11, pp. 13025-130462017.
[16] C. Qin, P. Ji, X. Zhang, J. Dong, and J. Wang, "Fragile image watermarking with pixel-wise recovery based on overlapping embedding strategy," Signal Processing, vol. 138, pp. 280-293, Sept. 2017.
[17] A. Shehab, M. Elhoseny, K. Muhammad, A. K. Sangaiah, P. Yang, H. Huang, and G. Hou, "Secure and robust fragile watermarking scheme for medical images," IEEE Access, vol. 6, pp. 10269-10278, 2018.
[18] F. Tohidi and M. Paul, "A new image watermarking scheme for efficient tamper detection, localization and recovery," in Proc. IEEE Int. Conf. on Multimedia & Expo Workshops, ICMEW'19, pp. 19-24, Shanghai, China, 8-12 Jul. 2019.
[19] F. Tohidi, M. Paul, M. R. Hooshmandasl, S. Chakraborty, and B. Pradhan, "Block-wise authentication and recovery scheme for medical images focusing on content complexity," in Proc. 10th Pacific-Rim Symp. on Image and Video Technology, pp. 86-99, Sydney, Australia, 18-22 Nov. 2019.
[20] A. M. Joshi, A. Darji, and V. Mishra, "Design and implementation of real-time image watermarking," in Proc. IEEE In. Conf. on Signal Processing, Communications and Computing, ICSPCC'11, 5 pp., Xi'an, China, 14-16 Sept. 2011.
[21] F. Tohidi, M. Paul, M. R. Hooshmandasl, T. Debnath, and H. Jamshidi, "Efficient self-embedding data hiding for image integrity verification with pixel-wise recovery capability," in Proc. Pacific-Rim Symp. on Image and Video Technology, pp. 128-141, Sydney, Australia, 18-22 Nov. 2019.
[22] Y. Xiang, D. Xiao, H. Wang, and X. Li, "A secure image tampering detection and self-recovery scheme using POB number system over cloud," Signal Processing, vol. 162, pp. 282-295, Sept. 2019.
[23] C. Kim and C. N. Yang, "Self-embedding fragile watermarking scheme to detect image tampering using AMBTC and OPAP approaches," Applied Sciences, vol. 11, no. 3, Article ID:. 1146, 2021.
[24] E. Gul and S. Ozturk, "A novel pixel-wise authentication-based self-embedding fragile watermarking method," Multimedia Systems, vol. 27, pp. 531-545, Jun. 2021.
