臺灣博碩士論文加值系統

目前現存的數位浮水印技術裡的最大挑戰就是對抵抗幾何攻擊能力的不足。幾何攻擊可以分為兩個類別：整體破壞，例如旋轉、位移；以及區域破壞，例如Stirmark標準攻擊。我們發現多種以抵抗幾何攻擊為本質而設計的數位浮水印技術，缺乏抵抗多重混合幾何攻擊的能力。在此篇論文中，我們將浮水印實作在灰階認證影像上，並提出一個利用區域三角網格的特徵點來定位以抵抗混合型幾何攻擊的強靭性數位浮水印。我們提出的方法可以重新定位被攻擊影像並且可與嵌入和認證浮水印程序獨立運作。我們使用的幾何不變機制與互補調變嵌入策略來提高對幾何攻擊的強靭性。最後，藉由實驗結果證明我們的方法對幾何攻擊的效果相當好。

The great challenge of existing watermarking methods is their limited resistance to the extensive geometric attacks. Geometric attacks can be decomposed into two classes: global distortion such as rotations and translations and local distortion such as the StirMark attack. We have found that the weakness of multiple watermark embedding methods that were initially designed to resist geometric attacks is their inability to withstand the combination of geometric attacks. In this thesis, the watermark is used in the gray-scale authentication image, and a robust image watermarking scheme is proposed that can withstand the geometric attacks through using local tri-mesh feature points. Our proposed method can re-synchronize the attacked images and is independent of the embedding and authentication process. The geometric invariant scheme is combined with the complementary modulation embedding strategy to enhance the resistance of geometric attacks. The experimental results verify that the proposed scheme is excellent for geometric attacks.

CHINESE ABSTRACT i
ABSTRACT ii
LIST OF FIGURES v
LIST OF TABLES vi
CHAPTER 1 INTRODUCTION 1
1.1 Motivation 1
1.2 Objectives 2
1.3 Thesis Organization 3
CHAPTER 2 BACKGROUND AND RELATED WORK 4
2.1 Digital Watermarking Techniques 4
2.1.1 Information Hiding 4
2.1.2 Categories of Watermark 5
2.1.3 Requirements of Watermark 7
2.1.4 Applications 9
2.2 Attacks on Watermarks 11
2.2.1 Removal Attacks 11
2.2.2 Geometric Attacks 11
2.2.3 Cryptographic Attacks 12
2.2.4 Protocol Attacks 13
2.3 Discrete Wavelet Transformation 14
2.4 Human Visual System Model in DWT Domain 16
2.4.1 Display Visual Resolution 16
2.4.2 Spatial Frequency 16
2.4.3 Detection Threshold 16
2.5 Complementary Modulation 18
2.5.1 The Behaviors of Transformed Coefficients under Attacks 18
2.5.2 Complementary Modulation Rules 18
2.6 Robust Feature Extraction 21
CHAPTER 3 OUR PROPOSED WATERMARKING METHOD 23
3.1 Watermark Encoding 23
3.1.1 Selection of Tri-mesh Feature Points 23
3.1.2 Normalization of Tri-mesh Feature Point Coordinates 25
3.1.3 Selection of Wavelet Coeffiecients 26
3.1.4 Bipolar Watermark Hiding 27
3.2 Watermark Decoding 29
3.2.1 Hotelling Transform 30
3.2.2 Rotation Detection 31
3.2.3 Scaling Detection 31
3.2.4 Flipping Detection 32
3.2.5 Watermark Detection 32
CHAPTER 4 EXPERIMENTAL RESULTS 35
4.1 Experimental Environment 35
4.2 Environmental Results 37
4.3 Comparison 42
CHAPTER 5 CONCLUSIONS AND FUTURE WORK 47
REFERENCES 48

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