在本篇論文中，我們提出基於特徵的多重目的影像浮水印演算法，可以同時達到影像認證與保護的功用。強健型浮水印通常使用於版權保護和所有權證明，而易碎型浮水印主要是用於內容認證和完整性證明。我們利用Hessian-Affine特徵擷取器分析出影像的特徵區域，接著再利用特徵區域中每個像素的方向性，將強健型浮水印藏入這些特徵區域中。另外，藉著易碎型嵌入方法採用知名的MD5與RSA加密演算法應用於非特徵區域，以達到影像認證的目的。因此使用本多重目的影像演算法嵌入的浮水印影像可以同時存在著強健型與易碎型浮水印資料。針對浮水印的強建性，我們利用許多惡意攻擊的方法測試本多重目的浮水印演算法，並跟現存的強健型浮水印演算法作比較，其本論文的實驗結果顯示本多重目的浮水印演算法有較好的效能，並且同時本浮水印演算法仍可以偵測出影像被竄改的位置。此外，實驗結果也顯示出我們的方法比現存其他多重目的浮水印演算法來的優越。

In this thesis, a feature-based multipurpose image watermarking algorithm is proposed to achieve the goal of image authentication and protection simultaneously. Copyright protection and ownership verification are usually performed by robust watermarks, and fragile watermarks are mainly applied to content authentication and integrity attestation. The proposed watermarking algorithm uses the Hessian-Affine feature detector to extract the characteristic regions of an image. Then the proposed robust embedded scheme exploits the local orientation of each pixel to embed the copyright watermarks in these characteristic regions. Furthermore, the remained non-characteristic regions are used for image authentication. The famous message digest 5 (MD5) and RSA encryption algorithms are adopted in the proposed fragile embedding scheme. Therefore robust and fragile watermarks are simultaneously existed in the watermarked image obtained by the proposed multipurpose image watermarking algorithm. For robustness, the existent robust watermarking algorithms are compared and many malicious attacks are also applied to our proposed watermarking algorithm. The experimental results show that our watermarking algorithm has better performance than others. The location of tampering in the proposed watermarked images can also be detected. Moreover, our experiment results also show that our watermarking algorithm is better than other different multipurpose image watermarking algorithms.

[1] B. Chen and G. W. Wornell, "Quantization Index Modulation Methods for Digital Watermarking and Information Embedding of Multimedia," Journal VLSI Signal Processing System for Signal, Image, and Video Technology, Vol. 27, pp. 7-33, Feb. 2001.
[2] C. Harris and M. Stephen, “A combined corner and edge detector,” in Proc. 4th Alvey Vision Conf., pp. 147-151, 1988.
[3] C. I. Podilchuk and W. Zeng, “Image-adaptive watermarking using visual models,” IEEE J. Select. Areas Commun., Vol. 16, pp. 525-539, May 1998.
[4] C. S. Lu, S. K. Huang, C. J. Sze, and H. Y. M. Liao, “Cocktail watermarking for digital image protection,” IEEE Trans. Multimedia, Vol. 2, pp. 209-224, Dec. 2000.
[5] C. Y. Lin, M. Wu, J. A. Bloom, I. J. Cox, M. L. Miller, and Y. M. Lui, “Rotation, scale and translation resilient watermarking for image,” IEEE Trans. Image Processing, Vol. 10, No. 5, pp. 767-782, May 2001.
[6] C. S. Lu, H. Y. Mark Liao, “Multipurpose watermarking for image authentication and protection,” IEEE Trans. Image Processing, Vol. 10, No. 10, pp. 1579-1592, Oct. 2001.
[7] C. S. Lu and C. Y. Hsu, “Content-dependent anti-disclosure image watermark,” Proc. 2nd Int. Workshop on Digital Watermarking, LNCS 2939, pp. 61-76, 2003.
[8] C. W. Tang and H. M. Hang, “A feature-based robust digital image watermarking scheme,” IEEE Trans. Signal Processing, Vol. 51, No. 4, pp. 950-959, April 2003.
[9] D. Coppersmith, F. Mintzer, C. W. Wu, and M. M. Yeung, “Fragile imperceptible digital watermark with privacy control,” in Proc. SPIE/IS&T Electronic Imaging Symp., Security, Watermarking Multimedia Contents, Jan 1999.
[10] D. Kundur and D. Hatzinakos, “Digital watermarking for telltale tamper proofing and authentication,” Proc. IEEE, Vol. 87, No. 7, pp. 1167-1180, July 1999.
[11] D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Computer Vision, Vol. 60, No. 2, pp.91-110, 2004.
[12] E. T. Lin, E. J. Delp, “Review of fragile image watermarks,” in Proc. of Multimedia and Security Workshop (ACM Multimedia ’99) , pp25-29, 1999.
[13] F. Mintzer and G. W. Braudaway, “If one watermark is good, are more better?” in Int. Conf. Acoustics, Speech, Signal Processing, pp. 2067-2070, 1999.
[14] Fabien A. P. Petitcolas, “Watermarking schemes evaluation,” IEEE Signal Processing, Vol. 17, No. 5, pp. 58–64, Sept. 2000.
[15] F. Deguilaume, S. Voloshynovskiy, T. Pun, “Secure hybrid robust watermarking resistant against tampering and copy attack,” Signal Processing, Vol. 83, pp. 2133-2170, 2003.
[16] G. L. Friedman, “The trustworthy digital camera: restoring credibility to the photographic image,” IEEE Trans. Consumer Electronics, Vol. 39, pp.905-910, Nov. 1993.
[17] G. Langelaar, R. Lagendijk, and J. Biemond, “Removing spatial spread spectrum watermarks by non-linear filtering,” in Proc. EUSIPCO, Vol. 4, pp. 2281-2284, 1998.
[18] H. Moravec, “Obstacle avoidance and navigation in the real world by a seeing robot rover,” Tech. Report CMU-RI-TR-3, Carnegie-Mellon University, Robotics Institute, Sept. 1980.
[19] H. Y. Lee, H. Kim and H. K. Lee, “Robust image watermarking using local invariant features,” Journal SPIE, Optical Engineering, Vol. 45, No. 3, 2006.
[20] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Trans. Image Processing, Vol. 6, No. 12, pp. 1673-1687, Dec. 1997.
[21] I. J. Cox, J.-P.M.G. Linnartz, “Some general methods for tampering with watermarks,” IEEE J. Selected Areas Commun., Vol. 16, No. 4, pp.587-593, May 1998.
[22] J. ÓRuanaidh, T. Pun, “Rotation, scale and translation invariant spread spectrum digital image watermarking,” Signal Processing, Vol. 66, No 3, pp. 303-317, May 1998.
[23] J. R. Hernández and F. Pérez-González, “Statistical analysis of watermarking schemes for copyright protection of images,” Proc. IEEE, Vol. 87, pp. 1142-1166, July 1999.
[24] J. S. Seo and C. D. Yoo, “Localized image watermarking based on feature points of scale-space representation,” Pattern Recognition, Vol. 37, pp. 1365-1375, 2004.
[25] J. Matas, O. Chum, M. Urban, T. Pajdla, “Robust wide-baseline stereo from maximally stable extremal regions,” Image and Vision Computing, Vol. 22, No. 10, pp. 761-767, 2004.
[26] K. Mikolajczyk and C. Schmid, “Scale and affine invariant interest point detectors,” Int. J. Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004.
[27] K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. V. Gool, “A comparison of affine region detectors,” Int. J. Computer Vision, Vol.65, pp. 43-72, 2006.
[28] M. M. Yeung and F. Mintzer, “An invisible watermarking technique for image verification,” In Proc. Int. Conf. Image Processing, May 1998.
[29] M. Kutter, “Watermarking Resisting to Translation, Rotation and Scaling,” Proc. SPIE Int. Sym. on Voice, Video, and Data Commun., Nov. 1998.
[30] M. Kutter, S. Voloshynovskiy, and A. Herrigel, “The watermark copy attack,” in Proc. SPIE Security Watermarking Multimedia Contents II, 2000.
[31] M. Holliman and N. Memon, “Counterfeiting attacks on oblivious block-wise independent invisible watermarking schemes,” IEEE Trans Image Processing, Vol. 9, No. 3, pp. 432-441, March 2000.
[32] M. U. Celik, G. Sharma, E. Saber, and A. M. Tekalp, “Hierarchical watermarking for secure image authentication with localization,” IEEE Trans Image Processing, Vol.11, No.4, pp. 585-595, April 2002.
[33] P. W. Wong, “A public key watermark for image verification and authentication,” in Proc. Int. Conf. Image Processing, vol. 1, pp. 455-459, 1998.
[34] P. W. Wong and N. Memon, “Secret and public key image watermarking schemes for image authentication and ownership verification,” IEEE Trans. Image Processing, Vol. 10, No. 10, pp.1593-1601, Oct. 2001.
[35] P. Bas, J-M. Chassery, and B. Macq, “Geometrically invariant watermarking using feature points,” IEEE Trans. Image Processing, Vol. 11, No. 9, pp. 1014-1028, Sept. 2002.
[36] S. Voloshynovskiy, A. Herrigel, N. Baumgartner, and T. Pun, “A stochastic approach to content adaptive digital image watermarking,” in Proc. 3rd Int. Workshop Information Hiding, pp. 211-236, Sept. 1999.
[37] S. Pereira, T. Pun, “Robust template matching for affine resistant image watermarks,” IEEE Trans. Image Processing, Vol. 9, No.6, pp. 1123-1129, June 2000.
[38] S. Pereira, T. Pun, “An iterative template matching algorithm using the Chirp-Z transform for digital image watermarking,” Pattern Recognition, Vol. 33, pp. 173-175, 2000.
[39] S. Voloshynovskiy, S. Pereira, V. Iquise, and T. Pun, “Attack modeling: towards a second generation watermarking benchmark,” Signal Processing, Vol. 81, pp. 1177-1214, 2001.
[40] T. Lindeberg and J. Garding, “Shape-adapted smoothing in estimation of 3-D shape cues from affine deformations of local 2-D brightness structure,” Image and Vision Computing, Vol. 15, No. 6, pp. 415-434, 1997.
[41] T. Tuytelaars and L.V. Gool, “Matching widely separated views based on affine invariant regions,” in Int. J. Computer Vision, Vol. 59, No. 1, pp. 61-85, 2004.
[42] T. Kadir, A. Zisserman, and M. Brady, “An affine invariant salient region detector,” in Proc. of the 8th European Conf. Computer Vision, pp. 404-416, 2004.
[43] Z. M. Lu, D. G. Xu, S. H. Sun, “Multipurpose image watermarking algorithm based on multistage vector quantization,” IEEE Trans. Image Processing, Vol. 14, No. 6, pp. 822-831, June 2005.