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研究生： 梁凱雯
Kai-Wen Liang
論文名稱： 基於特徵值空間分解之影像認證系統
Image Authentication System based on Eigenvalue Decomposition
指導教授： 張寶基
Pao-Chi Chang
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 通訊工程學系
Department of Communication Engineering
畢業學年度： 92
語文別： 英文
論文頁數： 65
中文關鍵詞： 浮水印 、影像認證 、數位簽章
外文關鍵詞： image authentication, digital signature, watermarking
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    • 在本篇論文中，我們提出基於特徵值空間分解影像認證系統，為期達到對一定範圍內之失真容忍度及區域性認證，此系統以區塊為單位計算影像係數值之統計特性，將區塊內之影像信號作特徵空間之分解，擷取其特徵值作為代表各區塊之數位簽章的來源，加密後傳送，接收端將解密後的特徵值用以認證所收到之影像資訊。
    我們將區塊先分成大小相同之子區塊，每一子區塊視為一隨機變數，各子區塊的大小作隨機變數之信號觀測空間以計算其期望值，進而對得到之信號空間作特徵值分解，取其最重要之一到數個特徵值作為一區塊之特徵代表。將取出之特徵代表經過量化後得到對應於各區塊之數位簽章，在認證端計算特徵之方式均與傳送端相同，唯在認證端的量化過程中在各量化區間的邊界處設一模糊區域用以容忍影像區塊之特徵值之小幅度變化。
    實驗結果證明此系統以區塊為單位並以特徵值擷取作為數位簽章的方法對於經過常見之影像處理後所造成的失真能達到一定的容忍度，並對於有意義之影像竄改能有高偵測率。

    In this thesis, we propose an image authentication system based on eigenvalue decomposition. In order to be incidental distortion tolerant and localization dominating, the feature is extracted on block based.
    The feature extracted from each block is depended on the statistical characteristic inside one block. Each block is first divided into sub-blocks with the same size. Each sub-block is considered as an observation signal space of a random variable. Each block has random variables that match the number of sub-blocks. The eigenvalue　decomposition operation is done within one image block. The feature is produced from the dominated eigenvalues. The feature is then quantized to generate the final signature for each block.
    In the receiver end, the feature of one image block is extracted from the same process in the transmission end, but it is quantized with a neutral zone. The neutral zone can tolerate the small change of the feature caused by the incidental distortions.
    The simulation results show that the proposed system works well in tolerating some kinds of image processing and achieves high detection accuracy.

    Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Image Authentication Related Researches 5 1.3 Organization 7 Chapter 2 Content Authentication Overview 8 2.1 Transmission Identity and Access Legality 8 2.1.1 Transmission Identity 8 2.1.2 Access Legality 9 2.1.3 Content Authentication 10 2.2 Requirements and Applications of Content Authentication 11 2.2.1 Exact Authentication 11 2.2.2 Selective- Authentication 13 2.2.3Localized Authentication 15 Chapter 3 Image Authentication Techniques 17 3.1 Categories of Image Authentication Techniques 17 3.1.1 Digital Signature Based Approach 17 3.1.2 Watermark-Based Approach 19 3.2 Techniques in Image Authentication 21 3.2.1 Feature Point-based 22 3.2.2 Quantization-based 23 3.2.3 Relation-based 23 Chapter 4 Image Authentication System Based on Eigenvalue Decomposition 24 4.1 System Architecture 24 4.1.1 Transmission End 25 4.1.2 Authentication End 26 4.1.3 Decision of Authentication Result 27 4.2 The Signature Generation Process 29 4.2.1 Block and Subblock Composition 29 4.2.2 Autocorrelation Matrix Construction 30 4.2.3 Eigenvalue Decomposition 33 4.2.4 Feature Extraction 37 4.2.5 Quantization of Block Feature 42 4.3 The Authentication Process 43 4.3.1 Neutral Zone 43 Chapter 5 Simulations and Analysis 45 5.1 Simulation Environment 45 5.2 Incidental Tolerance 48 5.2.1 JPEG compression 48 5.2.2 JPEG 2000 compression 51 5.2.3 Low Pass Filter 53 5.2.4 Medium Filter 56 5.3 Detection Accuracy of Malicious Tampering 58 Chapter 6 Conclusions 63 Bibliography 64

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