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研究生:蘇弘
研究生(外文):Hung Su
論文名稱:基於多維度直方圖可抗幾何及信號處理之浮水印技術
論文名稱(外文):Multi-dimensional Histogram-based Watermarking Scheme for Resisting Geometric and Signal Processing Attacks
指導教授:謝文雄謝文雄引用關係
指導教授(外文):Wen-Shyong Hsieh
學位類別:碩士
校院名稱:國立中山大學
系所名稱:資訊工程學系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:52
中文關鍵詞:幾何浮水印
外文關鍵詞:GeometricWatermarking
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近來,由於多媒體資料散佈的快速成長,有許多保護著作權的數位浮水印方案被提出。強軔性是浮水印其中的要點之一。但是,大多數傳統的浮水印方法,通常無法有效的同時抵抗幾何扭曲跟信號處理的攻擊。
要抵擋幾何攻擊可分為兩種不同的解決方式:非盲目與盲目的方法。在非盲目的研究中由於原始影像是已知的, 可藉由比對遭受攻擊的圖與原始影像來穫得良好的解決方案。而對於盲目的方法來說,由於無法使用原圖來做浮水印粹取的動作,明顯的將更具有挑戰性。
在這篇研究當中,我們題出了一個基於長條分佈圖特性且不須原圖就能粹取浮水印的方法。也就是我們提出一個新的方案,定義原始影像彩色空間的晶狀結構來藏匿浮水印的資料。我們藉由計算影像不同特性的長條分佈圖,並將其分佈圖等份切割為眾多動態區間。致使每個區間的內含相同數量的像素。然後,透過調整區間中各個像素的分佈來達到藏匿浮水印的工作。
由實驗的結果指出,這個方法可以有效的同時抵抗一般的幾何攻擊與大量的JPEG壓縮。
Many digital watermarking schemes have been proposed for copyright protection recently due to the rapid growth of multimedia data distribution. Robustness is one of the crucial important issues in watermarking. But, most of traditional digital watermarking schemes is normally not to resist both geometric distortion and signal processing attacks well.
There are two different types of solutions to resisting geometrical attacks: nonblind and blind methods. With the noblind approach, due to availability of the original image, the problem can be resolved with a good solution by elective search between the geometrically attacked and unattacked image. The blind solution, which does not use the original image in watermark extraction, is obviously more challenging.
In this research, we propose a blind watermarking scheme which based on histogram property. So that, we propose a novel scheme to define the lattice structure of color space of host image for embedding watermark data. We utilize the histograms of various properties that calculated from the host image, and partition each histogram space into several divisions with dynamic interval. The number of pixels of each division is equal. And then we embed watermark data by modifying distribution of each division.
The experimented results present the algorithm is robust to resist common geometric attacks and high quality JPEG compression at the same time.
Chapter 1 Introduction…………………………………………………...1
1-1 Background……………………………………………………………...…1
1-2 Motives and Objectives…………………………………………………….4
Chapter 2 Relevant Literature Discussion……………………….5
2-1 Invariant Domain Watermarking Scheme…………………………...……..5
2-1-1 �nIntegral Transform Invariants……………………………...……….6
2-1-1A �nThe Fourier Transform………………………………………7
2-1-1B Translation Invariance……………………………………….8
2-1-1C Rotation and Scale Invariance……………………………….8
2-1-1D Rotation, Scale and Translation Invariant…………………...9
���{���{���n�nWatermarking Implementation……………………………………..9
2-2 Template-Based Watermarking Scheme………………………………….11
���{���{���n�nWatermarking Embedding………………………………………...12
2-2-1.A Message Encoding and Training Sequence Embedding in the DWT Domain……………………………………………..13
2-2-1.B Template Embedding in DFT Domain……………………16
���{���{���n�nWatermark Extraction with Resynchronization…………………...17
2-2-2.A Template Detection…………………………………….....17
2-2-2.B Translation Registration and Decoding………………..….19
2-3 Feature-Based Watermarking Scheme…………………………................22
���{���{���n�nFeature Extraction…………………………………………………23
���{���{���n�nImage Normalization……………………………………………...24
���{���{���n�nWatermarking Embedding………………………………………...24
���{���{���n�nWatermarking Detection…………………………………………..25
Chapter 3 Proposed H istogram-Oriented Watermarking Algorithm………………………………………………………26
3-1 The methodology of Histogram-Oriented Watermarking Algorithm (HOWA)…………………………………………………………………...26
3-2 embedding process and extraction process…………………………….…34
3-2-1 Embedding process of Histogram-Oriented Watermarking Algorithm…………………………………………………………...35
3-2-2 Extraction process of HOWA……………………………………….37
Chapter 4 Experimental Results, Evaluation and Comparison…………………………………………………...38
Chapter 5 Conclusion and Future Work………………………...49
References……………………………………………………………………….50
[1] J.O’Ruanaidh and T. Pun, “Rotation, scale, and translation invariant digital image watermarking,” Signal Processing, vol. 66, no. 3, pp. 303-317,May 1998.
[2] C. Lin, M. Wu, J. Bloom, I. Cox, M. Miller, and Y. Lui, ”Rotation, scale, and translation resilient watermarking for images,” IEEE Trans. Image Processing, vol. 10, pp. 767-782, May 2001.
[3] D. Zheng, J. Zhao, and Abdulmotaleb El Saddik, “RST-invariant digital image watermarking based on log-polar mapping and phase correlation,” IEEE Trans. Circuits and Systems for Video Technology, vol. 13, no. 8, pp. 753-765, August 2003.
[4] Jae S. Lim. Two-Dimensional Signal and Image Processing. Prentice-Hall International, 1990.
[5] S. Pereira and T. Pun, “Robust template matching for affine resistant image watermarks,” IEEE Trans. Image Processing, vol. 9, pp. 1123-1129, June 2000.
[6] X. Kang, J. Huang, Y. Q. Shi, and Y. Lin, “A DWT-DFT composite watermarking scheme robust to both affine transform and JPEG compression,” IEEE Trans. Circuits and Systems for Video Technology, vol 13, no. 8, pp. 776-786, August 2003.
[7] M. Kutter, “Watermarking resistance to translation, rotation, and scaling, ” in Proc. SPIE Multimedia Systems and Applications, vol. 3528, pp.423-431, 1998.
[8] S. Voloshynovskiy, F. Deguillaume, and T. Pun, “Multibit digital watermarking robust against local nonlinear geometrical distortions,” in Proc. IEEE Int. Conf. Image Processing, Thessaloniki, pp. 999-1002, Oct. 2001.
[9] P. Bas, N. V. Boulgouris, F. D. Koravos, J.-M. Chassery,M. G. Strintzis, and B. Macq, “Robust watermarking of video objects for MPEG-4 applications,” in Proc. SPIE, Applications of Digital Image Processing XXIV, vol. 4472, pp. 85–94, Dec 2001.
[10] P. Bas, J.-M. Chassery, and B. Macq, “Image watermarking: an evolution to content based approaches,” Pattern Recognit., vol. 35, no. 3, pp. 545–561, Mar. 2002.
[11] M. Kutter, S. K. Bhattacharjee, and T. Ebrahimi, “Toward second generation watermarking schemes,” in Proc. IEEE Int. Conf. Image Processing, vol. 1, Kobe, Japan, pp. 320–323, Oct. 1999.
[12] N. Nikolaidis and I. Pitas, “Robust watermarking of facial images based on salient geometric pattern matching,” IEEE Trans. Multimedia, vol. 2, pp. 172–184, Sept. 2000. Signal Processing, vol. 2002, no. 4, pp. 418–431, Apr. 2002.
[13] 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.
[14] C. Harris and M. Stephen, “A combined corner and edge detector,” in Proc. 4th Alvey Vision Conf., 1988, pp. 147-151.
[15] J. Devars, C. Achard-Rouquet, and E. Bigorgne, “Un detecteur de point carateristiques sur des images multispectrals. Extension vers un detecteur sub-pixellique, “in Proc. GRETSI 99,Sept. 1999, pp. 627-630.
[16] S. M. Smith and J. M. Brady, “Susan- A new approach to low level image processing,” Int. J. Comput. Vis., vol.23, no. 1, pp. 45-78, May 1997.
[17] M. Alghoniemy and A. H. Tewfik, “Geometric distortion correction through image normalization,” in Proc. IEEE Int. Conf. Multimedia Expo., vol. 3, 2000, pp. 1291-1294.
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