Sayısal Görüntülerin Telif Hakkının Korunması İçin İris Tabanlı Biyometrik Damgalama Yaklaşımı

Abstract

Modern teknolojik gelişmeler, görüntü, ses, video ve metin gibi multimedya verilerinin yasadışı kopyalarının üretilmesini çok kolay hale getirmiştir. Sayısal damgalama teknikleri, telif hakkı korumalı veri dosyalarının yasadışı kullanımını önlemek amacıyla telif hakkı bilgilerinin korunacak ortama sayısal olarak gömülmesini amaçlar. Bu çalışmada, biyometrik verilerle sayısal görüntünün damgalanması yöntemi ele alınmıştır. Geleneksel damga yerine biyometrik özelliklerin kullanımı damgalama şemasının güvenliğini artırır. Bu çalışmada daha güvenli olması ve kopyalanmasının daha zor olması sebebiyle iris biyometrik verisi tercih edilmiştir. Kişinin göz görüntüsünden üretilen iris şablonu ayrık kosinüs dönüşümü ile ikili koda dönüştürülür. Bu ikili kod, orijinal görüntüye yeniden dağıtılmış değişmez ayrık dalgacık dönüşümü ve Schur ayrıştırma yardımıyla gömülür. İkili kodun gömülmesi için kullanılan bloklar standart sapma değerlerine bağlı olarak seçilir. Deneysel sonuçlar önerilen yöntemin algısal kalitesinin yüksek olduğunu ortaya koymuştur. Ayrıca farklı görüntü işleme atakları ve geometrik ataklar karşısında dayanıklılığı oldukça yüksek bulunmuştur.

Keywords

• Biyometrik Damgalama
• Yeniden Dağıtılmış Değişmez Ayrık Dalgacık Dönüşümü
• Schur Ayrıştırma
• Dayanıklılık

Iris-Based Biometric Watermarking Approach for Copyright Protection of Digital Images

Abstract

Modern technological advances has made it very easy to produce illegal copies of multimedia data such as image, audio, video, or text. Digital watermarking techniques aim to digitally embed copyright information into the media to be protected in an attempt to prevent illegal use of copyright protected data files. In this study, the method of digital image watermarking with biometric data is discussed. The use of biometric features instead of traditional watermarks increases the security of the watermarking scheme. Iris biometric data is preferred in this study because it is more secured and more difficult to copy. The iris template produced from the eye image of the person is converted into binary code via discrete cosine transform. This binary code is embedded into the cover image with the help of the redistributed invariant discrete wavelet transform and Schur decomposition. The blocks used for embedding binary code are selected based on their standard deviation values. Experimental results revealed that the perceptual quality of the proposed method is high. In addition, it is found to be highly robust against different types of image processing attacks as well as geometrical attacks. Keywords: Biometric Watermarking, Redistributed Invariant Discrete Wavelet Transform, Schur Decomposition, Robustness

Keywords

• Biometric Watermarking
• Redistributed Invariant Discrete Wavelet Transform
• Schur Decomposition
• Robustness

References

1. [1] Wójtowicz, W., Marek, R. O. 2016. Digital Images Authentication Scheme Based on Bimodal Biometric Watermarking In An Independent Domain, Journal of Visual Communication and Image Representation, Cilt. 38, s. 1-10.
2. [2] Majumder, S., Singh, A. D., & Mishra, M. 2009. A GUI Based Iris Authentication System For Secured Access. Int. Conf. Systemics, Cybernetics, Informatics (ICSCI-2009) under Pentagram Research, Hyderabad held, January, 7-10.
3. [3] Singh, P., Chadha, R. S. 2013. A Survey of Digital Watermarking Techniques, Applications and Attacks, International Journal of Engineering and Innovative Technology (IJEIT), Cilt. 2(9), s. 165-175.
4. [4] Zaiane, O., Mario, N., Stanley, O. 2002. Digital Watermarking: Status, Limitations and Prospects.
5. [5] Naderahmadian, Y., Hosseini-Khayat, S. 2014. Fast and Robust Watermarking In Still Images Based on QR Decomposition, Multimedia Tools and Applications, Cilt. 72(3), s. 2597-2618.
6. [6] Tao, H., Chongmin, L., Zain, J. M., Abdalla, A. N. 2014. Robust Image Watermarking Theories and Techniques: A review, Journal of Applied Research and Technology, Cilt. 12(1), s. 122-138.
7. [7] Li, L., Xu, H. H., Chang, C. C., Ma, Y. Y. 2011. A Novel Image Watermarking in Redistributed Invariant Wavelet Domain. Journal of Systems and Software, Cilt. 84(6), s. 923-929.
8. [8] Kazemivash, B., Moghaddam, M. E. 2017. A Robust Digital Image Watermarking Technique Using Lifting Wavelet Transform and Firefly Algorithm, Multimedia Tools and Applications, Cilt. 76(20), s. 20499-20524.

9. [9] Kazemivash, B., Moghaddam, M. E. 2018. A Predictive Model-based Image Watermarking Scheme Using Regression Tree and Firefly Algorithm, Soft Computing, Cilt. 22(12), s. 4083-4098.
10. [10] Kang, X. B., Zhao, F., Lin, G. F., & Chen, Y. J. 2018. A Novel Hybrid of DCT and SVD in DWT Domain for Robust and Invisible Blind Image Watermarking with Optimal Embedding Strength, Multimedia Tools and Applications, Cilt 77(11), s. 13197-13224.
11. [11] Liu, J. F., Huang, D. R., Hu, J. Q. 2003. The Orthogonal Wavelet Bases for Digital Watermarking, Journal of Electronics and Information Technology, Cilt. 25(4), s. 453-459.
12. [12] Hassanien, A. E. 2006. Hiding Iris Data for Authentication of Digital Images Using Wavelet Theory, Pattern Recognition and Image Analysis, Cilt. 16(4), s. 637-643.
13. [13] Majumder, S., Devi, K. J., & Sarkar, S. K. 2013. Singular Value Decomposition and Wavelet-based Iris Biometric Watermarking, IET Biometrics, Cilt. 2(1), s. 21-27.
14. [14] Lu, J., Qu, T., & Karimi, H. R. 2014. Novel iris biometric watermarking based on singular value decomposition and discrete cosine transform, Mathematical Problems in Engineering, 2014.
15. [15] Umar, M. M., Mehmood, A., Song, H., & Choo, K. K. R. 2017. I-Marks: An Iris Code Embedding System for Ownership Identification of Multimedia Content, Computers & Electrical Engineering, Cilt. 63, s. 209-219.
16. [16] Paunwala, M., & Patnaik, S. 2014. Biometric Template Protection with DCT-Based Watermarking, Machine Vision and Applications, Cilt. 25(1), s. 263-275.
17. [17] Singh, P., Raman, B., & Roy, P. P. 2017. A Multimodal Biometric Watermarking System For Digital Images in Redundant Discrete Wavelet Transform, Multimedia Tools and Applications, Cilt. 76(3), s. 3871-3897.
18. [18] Tarif, E. B., Wibowo, S., Wasimi, S., & Tareef, A. 2018. A Hybrid Encryption/Hiding Method for Secure Transmission of Biometric Data in Multimodal Authentication System, Multimedia Tools and Applications, Cilt. 77(2), s. 2485-2503.
19. [19] Su, Q., Niu, Y., Liu, X., Zhu, Y. 2012. Embedding Color Watermarks in Color Images Based on Schur Decomposition, Optics Communications, Cilt. 285(7), s. 1792-1802.
20. [20] Karajeh, H., Khatib, T., Rajab, L., Maqableh, M. 2019. A Robust Digital Audio Watermarking Scheme Based on DWT and Schur Decomposition, Multimedia Tools and Applications, Cilt. 78(13), s. 18395-18418.
21. [21] Su, Q., Chen, B. 2017. An Improved Color Image Watermarking Scheme Based on Schur Decomposition, Multimedia Tools and Applications, Cilt. 76(22), s. 24221-24249.
22. [22] Monro, D. M., Zhang, Z. 2005. An Effective Human Iris Code with Low Complexity. IEEE International Conference on Image Processing 2005, September, 277-280.
23. [23] Rakshit, S., Monro, D. M. 2006. Effects of Sampling and Compression on Human Iris Verification. 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, May, 337-340.
24. [24] Kalita, R., Majumder, S., Hussain, M. A. 2010. Multidimensional Multimetric Novel and Simple Techniques for Iris Recognition System, Int. J. Recent Trends Eng, Cilt. 3(3),s. 161-166.