跳到主要內容

臺灣博碩士論文加值系統

(44.222.64.76) 您好!臺灣時間:2024/06/15 06:23
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:何思亮
研究生(外文):He, Si-Liang
論文名稱:一種基於壓縮AMBTC的圖像認證及可恢復技術
論文名稱(外文):An Image Authentication Scheme Based on Compressed AMBTC with Restoration
指導教授:張真誠張真誠引用關係
指導教授(外文):Chang, Chin-Chen
口試委員:張真誠林家禎婁德權
口試委員(外文):Chang, Chin-ChenLin, Chia-ChenLou, Der-Chyuan
口試日期:2019-07-18
學位類別:碩士
校院名稱:逢甲大學
系所名稱:資訊工程學系
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:2019
畢業學年度:107
語文別:英文
論文頁數:69
中文關鍵詞:圖像驗證圖像壓縮基於像素基於龜殼的資訊隱藏脆弱水印竄改偵測霍夫曼編碼絕對值動量保留區塊截斷編碼
外文關鍵詞:image authenticationimage compressionpixel-basedturtle shell-based data hidingfragile watermarkingtamper detectionHuffman codingabsolute moment block truncation coding
相關次數:
  • 被引用被引用:1
  • 點閱點閱:231
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
在圖像中嵌入脆弱水印不只可以驗證其所有者的身分,還可以揭露遭到篡改的區域。本篇論文中分別提出了兩種不同的脆弱水印來達到基於像素的篡改偵測且仍保持好的影像品質。在第一個方法中,我們提出了絕對矩塊截斷編碼來設計一種基於像素的脆弱圖像水印方法。基於像素的篡改檢測和內容恢復機制在所提出的方案中協同應用,以增強可讀性,即使在圖像被篡改時也是如此。恢復資訊從原始圖像的絕對矩塊截斷編碼導出,並且認證碼由偽隨機亂數生成器產生。然後使用基於龜殼的數據隱藏方法將兩個數據離散地嵌入到水印圖像的兩個最低有效位中。因此,每一個非重疊像素對具有兩位恢復信息和兩位認證碼。當接收方懷疑所接收的圖像可能已被篡改時,認證碼可用於定位篡改的像素,然後恢復資訊可用於恢復篡改的像素。而第二個方法我們提出了一種量化區塊的壓縮算法,該算法結合了霍夫曼編碼和絕對矩塊截斷編碼。使用基於區塊的邊緣模式,提出了一種改進的絕對矩塊截斷編碼壓縮方法。它可以更有效地壓縮圖像並實現更高的壓縮比。而第三個方法則是結合了第一個方法中的數據隱藏方法和第二個方法的壓縮算法而成的脆弱圖像水印方法,利用基於霍夫曼編碼的絕對矩塊截斷編碼對恢復資訊再壓縮,並同時將其作為驗證碼使用。實驗結果表明,我們的方法在影像品質上優於幾種最先進的脆弱水印。
Embedding a fragile watermark in an image not only verifies the identity of its owner, it also reveals areas that have been tampered with. In this paper, two different fragile watermarks are proposed to achieve pixel-based tamper detection and still maintain good image quality. In the first method, we propose an absolute moment block truncation coding(AMBTC) to design a pixel-based fragile image watermarking method. Pixel-based tampering detection and content recovery mechanisms are collaboratively applied in the proposed scheme to enhance readability even when images have been tampered. Recovery information is derived from the AMBTC compression codes of the original image, and authentication codes are generated by a pseudo random generator (PRG). Both data are then discretely embedded into two LSB of a watermarked image with turtle shell-based data hiding method. Therefore, each non-overlapped pixel pair have 2 bits of recovery information and 2 bits of authentication code. When the recipient suspects that the received image may have been tampered with, the authentication code can be used to locate tampered pixels, and then the recovery information can be used to restore the tampered pixels. In the second method, we propose a quantization block compression algorithm that combines Huffman coding and absolute moment block truncation coding. Using the block-based edge pattern, an improved absolute moment block truncation coding compression method is proposed called HC-AMBTC for short. It can compress images more effectively and achieve a higher compression ratio. The experimental results showed that the compression ratio of this algorithm was better than several of the most advanced compression algorithms. Experimental results show that our two methods outperform several of the most advanced compression algorithms in image quality.
摘 要 i
Abstract ii
Table of Contents iii
List of Figures iv
List of Tables v
Chapter 1. Introduction 1
1.1 Motivation 1
1.2 Thesis Organization 4
Chapter 2. Pixel-based fragile image watermarking based on absolute moment
block truncation coding 5
2.1 Proposed Scheme 5
2.1.1 Watermarking Embedding 5
2.1.2 Detection and Recovery of Tampered Area 11
2.2 Experimental Results 14
2.3 Discussion 24
Chapter 3. HC-based absolute moment block truncation coding 26
3.1 Proposed Scheme 26
3.2 Experimental Results 28
3.3 Discussion 36
Chapter 4. Pixel-based fragile image watermarking based on HC absolute
moment block truncation coding 38
4.1 Proposed Scheme 38
4.1.1 Watermarking Embedding 38
4.1.2 Pixel based Detection and Recovery of Tampered Area 43
4.2 Experimental Results 45
4.3 Discussion 52
Chapter 5. Conclusions and Future Work 54
References 56

[1] E. Delp, O. Mitchell, “Image Compression Using Block Truncation Coding,” IEEE Transactions on Communications, Vol. 27, Issue 9, pp. 1335-1342, Sep. 1979.
[2] M. Lema, O. Mitchell, “Absolute Moment Block Truncation Coding and Its Application to Color Images,” IEEE Transactions on Communications, Vol. 32, Issue 10, pp. 1148-1157, Oct. 1984.
[3] I. Kaspar Raj, “Image Data Hiding in Images Based on Interpolative Absolute Moment Block Truncation Coding,” Mathematical Modelling and Scientific Computation, Vol. 283, pp. 456-463, Mar. 2012.
[4] C.C. Chang, Y.J. Liu, T.S. Nguyen, “A Novel Turtle Shell based Scheme for Data Hiding,” Intelligent Information Hiding and Multimedia Signal Processing, pp. 89-93, Aug. 2014.
[5] Y.J. Liu, C.C. Chang, T.S. Nguyen, “High Capacity Turtle Shell-based Data Hiding,” IET Image Processing, Vol. 10, Issue 2, pp. 130-137, Feb. 2016.
[6] J. Fridrich, M. Goljan, “Images with Self-correcting Capabilities,” Proceedings of International Conference on Image Processing, pp. 792-796, Oct. 1999.
[7] X.Z. Zhu, T.S. Ho, P. Marziliano, “A New Semi Fragile Image Watermarking with Robust Tampering Restoration Using Irregular Sampling,” Signal Processing on Image Communication, Vol. 22, Issue 5, pp. 515-528, Jun. 2007.
[8] X.P. Zhang, S.Z. Wang, “Fragile Watermarking with Error-free Restoration Capability,” IEEE Transactions on Multimedia, Vol. 10, Issue 8, pp. 1490-1499, Dec. 2008.
[9] X.P. Zhang, S.Z. Wang, Z.X. Qian, “Reference Sharing Mechanism for Watermark Self-Embedding,” IEEE Transactions on Image Processing, Vol. 20, Issue 2, pp. 485-495, Feb. 2011.
[10] X.P. Zhang, S.Z. Wang, G.R. Feng, “Fragile Watermarking Scheme with Extensive Content Restoration Capability,” International Workshop on Digital Watermarking, pp. 268-278, 2009.
[11] S.S. Yang, C. Qin, Z.X. Qian, “Tampering Detection and Content Recovery for Digital Images Using Halftone Mechanism,” Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 130-133, Aug. 2014.
[12] C. Qin, P. Ji, X.P. Zhang, J. Dong, J.W. Wang, “Fragile Image Watermarking with Pixel-wise Recovery Based on Overlapping Embedding Strategy,” Signal Processing, Vol. 138, pp. 280-293, Sep. 2017.
[13] C.W. Yang, J.J. Shen, “Recover the Tampered Image Based on VQ Indexing,” Signal Processing, Vol. 90, Issue 1, pp. 331-343, Jan. 2010.
[14] T.Y. Lee, S.F. Lin, “Dual Watermark for Image Tamper Detection and Recovery,” Pattern Recognition, Vol. 41, Issue 11, pp. 3497-3506, Nov. 2008.
[15] K. K. Gola, B. Gupta, Z. Iqbal, “Modified RSA Digital Signature Scheme for Data Confidentiality,” International Journal of Computer Applications, Vol. 106, No. 13, pp. 13-16, Nov. 2014.
[16] National Institute of Standards and Technology, “Secure Hash Standard (SHS),” Federal Information Processing Standards 180–3, Aug. 2015.
[17] W. Stallings, Cryptography and Network Security Principles and Practices, 7th Edition, Pearson Education, Oct. 2016.
[18] H. Zhang, C.Y. Wang, X. Zhou, “Fragile Watermarking for Image Authentication Using the Characteristic of SVD,” Algorithms, Vol. 10, Issue 1, pp. 1-12, Feb. 2017.
[19] V.S. Dhole, N.N. Patil, “Self Embedding Fragile Watermarking for Image Tampering Detection and Image Recovery Using Self Recovery Blocks,” International Conference on Computing Communication Control and Automation, pp. 752-757, Feb. 2015.
[20] D. Singh, S. Shivani, S. Agarwal, “Self-embedding Pixel Wise Fragile Watermarking Scheme for Image Authentication,” International Conference on Intelligent Interactive Technologies and Multimedia, Vol. 10, Issue 1, pp. 111-122, 2013.
[21] C. Qin, C.C. Chang and P.Y. Chen, “Self-embedding Fragile Watermarking with Restoration Capability based on Adaptive Bit Allocation Mechanism,” Signal Processing, Vol. 92, Issue 4, pp. 1137-1150, Apr. 2015.
[22] C. Qin, H.L. Wang, X.P. Zhang, X.M. Sun, “Self-embedding Fragile Watermarking based on Reference-data Interleaving and Adaptive Selection of Embedding Mode,” Information Sciences, Vol. 373, pp. 233-250, Dec. 2016.
[23] B. Zeng, Y. Neuvo, “Interpolative BTC Image Coding with Vector Quantization,” IEEE Transactions on Communications, Vol. 41, Issue 10, pp. 1436-1438, Oct. 1993.
[24] R. M. Gray, “Vector Quantization,” IEEE ASSP Magazine, Vol. 1, Issue 2, pp. 4-29, Apr. 1984.
[25] Int. Telecommunication Union, CCITT Recommendation T.81, Information Technology, “Digital Compression and Coding of Continuous-tone Still Images-Requirements and Guidelines,” 1992.
[26] D. A. Huffman, “A Method for the Construction of Minimum-Redundancy Codes,” Proceedings of the IRE, Vol. 40, Issue 9, pp. 1098-1101, Sep. 1952.

電子全文 電子全文(本篇電子全文限研究生所屬學校校內系統及IP範圍內開放)
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊