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研究生:謝依蓓
研究生(外文):Yi-Pei Hsieh
論文名稱:嵌入機密訊息於數位影像及其壓縮碼之技術
論文名稱(外文):Embedding Secrets in Digital Images and Their Compression Codes
指導教授:張真誠張真誠引用關係
指導教授(外文):Chin-Chen Chang
學位類別:博士
校院名稱:國立中正大學
系所名稱:資訊工程所
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:2009
畢業學年度:97
語文別:英文
論文頁數:120
中文關鍵詞:資訊隱藏可逆式資訊隱藏影像隱藏機密影像分享影像認證
外文關鍵詞:Data hidingreversible data hidingimage authenticatioinimage hidingsecret image sharing
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網路技術的蓬勃發展使得人們可以透過網際網路互相傳遞與分享各類資訊,但是直接在網路上傳送重要機密資訊是危險的行為,因此,保護資訊安全衍然變成近年來最重要的議題。為了確保資訊安全,很多研究投注心力在資訊隱藏領域(data hiding),資訊隱藏技術將機密資訊隱藏於掩護媒體(cover carrier),如文字、影像、聲音、視訊或是壓縮碼等,而產生偽裝媒體(stego medium),此技術目前已被運用在許多應用上,譬如秘密傳輸(secret data transmission)、著作權保護(copyright protection)、資料驗證(content authentication)及註解藏匿(annotation embedding)等。在本論文中,我們將致力於發展四個資訊隱藏方法來達到機密資訊的安全傳輸與重要資訊的保護。
在本論文的前兩個資訊隱藏方法中,是以數位影像作為掩護媒體來藏入機密影像,藉此保護機密影像的安全。第一個影像隱藏方法(image hiding)植基於向量量化編碼法(vector quantization)的觀念,利用結合兩本編碼簿(two-codebook)、三階段區塊對應(three-phase block matching)與模數函數替換(modulus substitution)等策略,不但確保多張尺寸大的機密影像能被藏入一張尺寸小的掩護影像(cover image),而且維持偽裝影像(stego image)與取出之機密影像的視覺品質。然而,使用影像隱藏方法只以一張偽裝影像來保護機密影像,一旦此偽裝影像被破壞,則無法取出機密影像,因此,在第二個資訊隱藏方法中,我們結合影像隱藏、機密影像分享與影像驗證等技術來保護機密影像,其中機密影像分享技術是植基於Thien-Lin的方法,而影像驗證法則是利用中國餘數定理(Chinese remainder theorem)來實作。
一般來說,數位影像會先經過壓縮,以節省網路頻寬及加速傳輸效能。在影像壓縮技術中,向量量化編碼法具有架構簡單、易實作及有效率的解碼速度等優點,是最常採用的一種影像壓縮法。所以,在本論文中,後兩個資訊隱藏方法是以影像的向量量化編碼表(index table)作為掩護媒體來藏入機密資訊,這兩個方法皆具有可逆能力(reversibility),換句話說,在機密資訊被取出後,原始的向量量化編碼表能被完整的回復。其中第一個方法乃藉由使用循次序編碼法(search-order coding)、邊緣吻合向量量化編碼法(side-match vector quantization)及向量量化編碼法等三種不同的編碼法來藏入機密資訊到向量量化編碼表。然而,此方法只能藏入少量的機密資訊,所以,第二個方法的精神主要利用影像中空間區域相似性的特性,使用反叢聚(declustering)與卡笛生乘積(Cartesian product)等技術來提高機密資訊的藏量。
本論文所提出之方法的效能都已經由實驗進行評估,實驗結果證明我們提出的這四個資訊隱藏技術皆優於先前發表的文獻方法。
The rapid advance of computer networks enables people to distribute information of various types across the Internet and to share them without the physical location restriction. However, transmitting important and confidential information through the Internet barely is very dangerous. Thus, the issue of protecting information security becomes crucial and significant over the past years. Among information security protecting methods, one of the attractive methods is data hiding. Data hiding is a technique of embedding secrets into a cover carrier, such as texts, images, audios, videos and compressed codes, to generate a stego medium for achieving secret data transmission, copyright protection, content authentication and annotation embedding. In this dissertation, we aim to design several data hiding schemes with different domains to solve the problems of secure transmission and protection of secret information.
The research begins with developing two hiding schemes by taking images as the cover media for the sake of protecting image-based secrets. The first image hiding scheme is proposed based on the concept of vector quantization (VQ). In our VQ framework, the strategies of two-codebook combination, three-phase block matching, and modulus substitution are presented to not only ensure that multiple secret images with large sizes can be embedded into a cover image with small size but also maintain good qualities in the stego image and the extracted secret images. However, applying such an image hiding technique can only protect the secret images in a single stego image. Once the stego image is broken, the secret images are lost. For avoiding such a situation, we thereby combine the concept of image hiding with secret image sharing and image authentication in the second hiding scheme to protect the secret images. Here, the secret image sharing is based on Thien and Lin’s scheme and the image authentication is implemented with Chinese remainder theorem.
In general, images are compressed for the purpose of saving bandwidth and speeding up delivery. Vector quantization is one of the most commonly used compression methods for digital images due to its simple architecture, and efficient decoding procedure. Therefore, in this dissertation, the last two hiding schemes are introduced to use the VQ compression codes (i.e., indices of the index table) as the cover media to embed secret data. The two schemes are all with reversibility property. That is, the original compressed codes can be recovered after the extraction of hidden data. The first one applies three different coding methods, search-order coding, side-match vector quantization, and vector quantization, to imply the secret bits. However, such a hiding method is capable of embedding a small amount of secrets. Therefore, the second scheme uses the similarity property of adjacent areas and combines the techniques of declustering and Cartesian product to improve the embedding capacity.
The performances of all the aforementioned proposed methods have been evaluated via some experiments. The experimental results support that they are indeed superior to other state-of-the-art methods.
中文摘要 i
Abstract iii
List of Figures vii
List of Tables ix
Chapter 1 Introduction 1
1.1 RESEARCH MOTIVATION 1
1.2 RESEARCH SCORE AND OBJECTIVES 3
1.3 ORGANIZATION 5
Chapter 2 Related Techniques 6
2.1 IMAGE COMPRESSION TECHNIQUES 6
2.1.1 Vector Quantization (VQ) 6
2.1.2 Side Match Vector Quantization (SMVQ) 7
2.1.3 Search-Order Coding (SOC) 9
2.2 DATA HIDING 11
2.3 REVERSIBLE DATA HIDING 14
2.3.1 Chang et al.’s Method 16
2.3.2 Chang and Lin’s Method 17
2.4 IMAGE HIDING 19
2.5 SECRET IMAGE SHARING 21
2.5.1 Thien and Lin’s scheme 24
2.5.2 Lin and Tsai’s scheme 25
2.5.3 Yang et al.’s scheme 28
2.6 LINDE-BUZO-GRAY (LBG) ITERATIVE ALGORITHM 29
2.7 CHINESE REMAINDER THEOREM (CRT) 30
Chapter 3 A Two-Codebook Combination and Three-Phase Block Matching Based Image Hiding Scheme with High Embedding Capacity 32
3.1 THE PROPOSED METHOD 32
3.1.1 The Codebook Generating Procedure 33
3.1.2 The Three-phase Block Matching Procedure 35
3.1.3 The Embedding and Extracting Procedures 39
3.2 EXPERIMENTAL RESULTS AND DISCUSSIONS 42
3.3 SUMMARIES 50
Chapter 4 Sharing Secrets in Stego Images with Authentication 51
4.1 THE PROPOSED METHOD 51
4.1.1 Sharing and embedding procedure 52
4.1.2 Authentication and revealing procedure 55
4.2 EXPERIMENTAL RESULTS AND DISCUSSIONS 56
4.3 SUMMARIES 60
Chapter 5 Three-Phase Lossless Data Hiding Method for the VQ Index Table 62
5.1 THE PROPOSED METHOD 62
5.1.1 The Data hiding Procedure for RSOCSM 63
5.1.2 The Data Extracting Procedure for RSOCSM 66
5.2 EXPERIMENTAL RESULTS AND DISCUSSIONS 67
5.3 SUMMARIES 72
Chapter 6 Lossless Data Embedding with High Embedding Capacity Based on Declustering for VQ-Compressed Codes 73
6.1 THE PROPOSED METHOD 73
6.1.1 The Declustering Procedure 73
6.1.2 The Embedding Procedure 77
6.1.3 The Extraction and Recovery Procedures 81
6.2 EXPERIMENTAL RESULTS AND DISCUSSIONS 83
6.3 SUMMARIES 92
Chapter 7 Conclusions and Future Works 94
References 97
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