隨著電腦與網際網路持續的發展創新，科技帶給人們的便利就不斷的衝擊人類社會，人與人之間資訊的交流比早期電腦還未發展時來的更加的容易且頻繁。但也因為如此，竊取、修改他人資訊也變得比以往簡單太多，不肖人士利用電腦及網路即可非法取得資料，因此如何防堵資料被偷竊與竄改就顯得非常重要。數位浮水印技術是一種將個人資訊加入到欲保護的媒體中的方法，日後受保護的媒體產生爭議時，便可取出以證明其所有權，達到保護資產與驗證所有權目的。本研究以視覺密碼為基礎，應用統計學中大數法則所帶來的守恆特性產生視覺密碼所需要的分享影像。本研究的優點有三個：一，我們的方法以頻率域的方式嵌入浮水印，產生不擴展的分享影像，降低了像素值易受攻擊的影響。二，驗證所有權的過程不需要原圖的輔助即可取出浮水印。三，解決了保護影像被攻擊後的浮水印強韌性不佳的問題。實驗結果證明，本研究對於dark、light、blur、sharpen、noise、distort、jitter、jpeg、crop等攻擊有優異的抵抗性。

Because computer technology is developed so fast, people enjoy the convenience it brings to us everyday. On the other hand, hackers may access the confidential data illegally and easily by the computer and the Internet. Therefore, how to protect these important data against being stolen or modified is an essential issue.
Digital watermark is a method which is to add a personal information into an intellectual property to protect its’ ownership right. When someday the intellectual property is disputed, the owner can retrieve the watermark and prove their ownership right.
Our study based on the properties of visual cryptography and statistics to generate the shares during the processes of embedding and verifying the hidden watermark. There are three advantages of our study. 1. We embedded the watermark by frequency domain and created unexpanded shares, which reduced the impact of pixel modification effectively. 2. Our method does not require the help of the original image during the verification process. 3. We solve the robustness problem when protected image suffered from attack. Experimental results indicated that our method had a good robustness on dark, light, blur, sharpen, noise, distort, jitter, jpeg, and crop attacks.

目錄
第一章 緒論	1
1.1 前言：	1
1.2 研究目的：	3
1.3 論文架構：	3
第二章 文獻探討	4
2.1 視覺密碼：	4
2.2浮水印技術	8
2.3 HAAR離散小波轉換(HAAR DISCRETE WAVELET TRANSFORM; DWT)	12
2.4視覺密碼應用於浮水印技術	15
第三章  應用統計特性於數位影像保護	20
3.1 統計守恆	20
3.2 最高位元平面	21
3.3 樣本平均數	22
3.3.1 中央極限定理(Central Limit Theorem, CLT)	22
3.3.2 常態分配	23
3.4 樣本像素配對	25
3.4.1 大數法則	25
3.4.2 樣本像素配對	26
3.5 本研究的理論基礎	27
3.5.1 數位資產所有權產生過程：	28
3.5.2 資產所有權驗證步驟：	30
3.6 驗證取出之浮水印的相似程度	32
3.7 驗證原圖與受攻擊後的影像相似程度	33
第四章 實驗結果與討論	35
4.1 實驗環境	35
4.2 以不同的受保護影像來驗證本研究的正確性：	35
4.3 攻擊實驗	36
4.3.1 Light攻擊	37
4.3.2 Dark攻擊	39
4.3.3 Blur攻擊	41
4.3.4 Sharpen攻擊	43
4.3.5 Noise攻擊	45
4.3.6 Distort攻擊	47
4.3.7 Jitter攻擊	49
4.3.8 Jpeg攻擊	51
4.3.9 Crop攻擊	53
4.4	與黃培修作比較	55
第五章 結論	57
參考文獻	58

表目錄
表 1 視覺密碼模型.................................................................................................................5
表 2 像素分享模型...............................................................................................................6
表 3 Fang 的分享機制..........................................................................................................7
表 4 官振宇之機密影像分享矩陣.......................................................................................8
表 5 浮水印分類...................................................................................................................9
表 6 沈昌興的黑白視覺密碼模型.....................................................................................22
表 7 Hsu 之視覺密碼加密規則.........................................................................................24
表 8 黃培修的浮水印分享規則.........................................................................................27
表 9 浮水印的產生與驗證.................................................................................................36
表 10 Light 攻擊實驗結果.................................................................................................38
表 11 Dark 攻擊實驗結果..................................................................................................40
表 12 Blur 攻擊實驗結果...................................................................................................42
表 13 Sharpen 攻擊實驗結果.............................................................................................44
表 14 Noise 攻擊實驗結果................................................................................................46
表 15 Distort 攻擊實驗結果...............................................................................................48
表 16 Jitter 攻擊實驗結果..................................................................................................50
表 17 Jpeg 攻擊實驗結果..................................................................................................52
表 18 Crop 攻擊實驗結果..................................................................................................54

圖目錄
圖 1 基礎矩陣.......................................................................................................................4
圖 2 像素分享矩陣...............................................................................................................4
圖 3 灰階影像..................................................................................................................... 11
圖 4 水平分割.....................................................................................................................13
圖 5 垂直分割.....................................................................................................................13
圖 6 三階Haar 小波轉換後的頻率區塊...........................................................................14
圖 7 Hsieh 等人的Mapping Table .....................................................................................16
圖 8 Lou 等人所提出的密碼簿(codebook) .......................................................................17
圖 9 視覺密碼應用於浮水印之模型.................................................................................18
圖 10 數位資產驗證過程.....................................................................................................19
圖 11 樣本均數分配.............................................................................................................23
圖 12 浮水印嵌入過程.........................................................................................................29
圖 13 影像驗證過程.............................................................................................................32
圖 14 受保護影像(512×512) (a) Lena (b) Food (c) Flower (d) Mario.................................35
圖 15 浮水印影像(256×256) ................................................................................................35
圖 16 Lena 影像攻擊與黃培修的比較..............................................................................55
圖 17 Food 影像攻擊與黃培修的比較..............................................................................55
圖 18 Flower 影像攻擊與黃培修的比較...........................................................................56
圖 19 Mario 影像攻擊與黃培修的比較............................................................................56

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