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研究生：	王亮丰 Wang, Liang-Feng
論文名稱：	使用小波轉換之基因式浮水印隱藏技術 Genetic Watermark Embedding Based on Wavelet
指導教授：	陳進興 Chen, Chin-Hsing
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2004
畢業學年度：	92
語文別：	英文
論文頁數：	66
中文關鍵詞：	浮水印、量化、錯誤控制碼
外文關鍵詞：	Error Control Code, Watermark, Quantization
相關次數：	點閱：80 下載：2
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　　由於網路的快速發展，數位化的內容可以容易的被取得，複製與竄改，因此網路上智慧財產權(IP)變得更重要。數位浮水印是一種保護智慧財產權安全且可信賴的方法。

　　在本論文提出一個以離散小波轉換(DWT)為基礎的數位浮水印系統。首先，原始影像(Cover Image)與浮水印影像(Logo Image)分別經過2階與1階小波轉換到頻率域。在小波轉換之後，利用SVD來挑選浮水印的特徵值，稱之為浮水印元素(特徵值)。此浮水印特徵值接著被量化與編碼((7,4)漢明碼)而形成浮水印碼。每個浮水印碼又被擴展成5位元的PN碼而形成浮水印PN序列。結合了(7,4)漢明碼與PN碼，我們所提出的架構有二次錯誤更正的能力。為了保密，我們重新排列原始影像的方塊去破壞原始影像每個次頻帶係數間的關係，而且再把每個方塊內的係數取絕對值，係數排序，分成7等份。最後，利用基因演算法可適性地來選擇一組好的原始影像係數來嵌入浮水印。

　　實驗結果顯示我們提出的架構在不同的攻擊下取回的浮水印能有好的品質。而加入浮水印後的影像其PSNR值皆大於25dB。

　　Because the rapid development of Internet, digitized content can be accessed, duplicated and altered easily, therefore intellectual property (IP) of Internet became more and more important. Digital watermarking is one kind of methods for protecting intelligence proprietary security.

　　In this thesis, a watermarking system based on Discrete Wavelet Transform (DWT) is proposed. To begin with, we transform the original image (Cover image) and the watermark image (Logo image) from the spatial domain to the frequency domain by using 1-scale and 2-scale equal band DWT respectively. After the transformation, we use SVD to choose the feature of watermark, which is referred to as the watermark element (feature). The watermark feature is then quantized and encoded ((7,4) Hamming code) to form a watermark code. Each watermark code is then spreaded by 5 bits PN code to form a watermark PN sequence. To combine (7,4) Hamming code and PN code, our scheme has ability of double error correction. For security, we rearrange blocks of the original image to break down the relationship of the coefficients in each subband, and take absolute value, sort and divide into 7 parts in each block. Finally, we used the genetic algorithm to choose a fine group coefficients of the original image adaptively for embedding the watermark.

　　Experimental results show that the proposed scheme can obtain good quality extracted watermarks under various attacks. The PSNR values of the watermarked image of Lena and Texture are more than 25dB.

Abstract..........................................I

Contents........................................III

Figure Captions..................................VI

Table Captions...................................IX

Chapter 1	Introduction......................1
1	Motivation........................1
2	Contribution......................1
3	Organization of the Thesis........2

Chapter 2	Overview of Image Watermarking....3
1	Generic Watermarking System.......3
2	Characteristics of Watermarking...5
3	Terminology of Watermarking.......7
4	Previous Watermarking Techniques..8
4.1 Least Significant Bits (LSB) in the Spatial Domain..............................8
4.2 Discrete Cosine Transform in the Frequency Domain..............................9
4.3 Discrete Wavelet Transform in the Frequency Domain.............................12
	
Chapter 3	Techniques Used in the Proposed Watermarking Scheme......................14
1	Wavelet Transform................14
1.1 Pyramidal Discrete Wavelet Transform........................................15
1.2 Equal Band Discrete Wavelet Transform........................................16
1.3 Equal Band DWT Block Rearrangement....................................18
2	Singular Value Decomposition.....19
3	Quantization.....................20
3.1 Uniform Quantization.......20
3.2 Non-uniform Quantization...23
4	Error Control Code...............26
4.1 Linear Block Encoder.......26
4.2 Linear Block Decoder.......29
5	PN Code in Spread Spectrum.......33
6	Genetic Algorithms (GAs).........35
6.1 Initialization.............35
6.2 Evaluation.................39
6.3 Selection..................41
6.4 Crossover..................41
6.5 Mutation...................42
7  Rotation Mask.......................43

Chapter 4	The Proposed Watermarking Scheme.............45
1	Watermark Embedding Process......45	
2	Watermark Extraction Process.....48	
	
Chapter 5	Experimental Results and Conclusions	.................................51
1	Quantitative Measurement of Performance......................................51	
2	Experimental Results.............52
2.1 Cropping Attack............54
2.2 Uniform Noise Attack.......56
2.3 Edge Enhance Attack........57
2.4 Blur Attack................58
2.5 Sharpen Attack.............59
2.6 Histogram Equalize Attack..60
2.7 Rotation Attack............61
2.8 JPEG Attack................62
3	Conclusions......................63
		
References.......................................64

                                    

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[10] C. A. Murthy, Nirmalya Chowdhury, “In Search of Optimal Clusters Using Genetic Algorithms”, Pattern Recognition Letters, pp. 825-832, Mar. 1996.

[11] Jerome M. Shapiro, “Embedded Image Coding Using Zerotrees of Wavelet Coefficients”, IEEE Trans. on Signal Processing, Vol. 41, No. 12, pp. 3445-3462, Dec. 1993.

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[13] Houng-Jyh Mike Wang, Po-Chyi Su and C.-C. Jay Kuo, “Wavelet-Based Digital Image Watermarking”, Optics Express, Vol. 3, No. 12, pp.491-496, Dec. 1998.

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校內：2007-08-13公開
校外：2007-08-13公開

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