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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44279完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李明穗 | |
| dc.contributor.author | Yu-Hsiang Chiu | en |
| dc.contributor.author | 邱鈺翔 | zh_TW |
| dc.date.accessioned | 2021-06-15T02:48:40Z | - |
| dc.date.available | 2009-08-12 | |
| dc.date.copyright | 2009-08-12 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08-06 | |
| dc.identifier.citation | [1] J. Lichtenauer, I. Setyawan, T. Kalker, and R. Lagendijk, “Exhaustive geometrical
search and the false positive watermark detection probability,” SPIE, Security and Watermarking of Multimedia Contents, pp. 203–214, January 2003. [2] P. Dong, J. Brankov, N. Galatsanos, and Y. Yang, “Geometric robust watermarking through mesh model based correction,” IEEE International Conference on Image Processing, vol. 3, pp. 493–496, September 2002. [3] P. Dong, J. B. G. Brankov, N. P. Galatsanos, Y. Yang, and F. Davoine, “Digital watermarking robust to geometric distortions,” IEEE Transactions on Image Processing, pp. 2140–2150, 2005. [4] D. Coltuc and P. Bolon, “Robust watermarking by histogram specification,” IEEE International Conference of Image Processing, pp. 236–239, October 1999. [5] C. Y. Lin, M. Wu, J. A. Bloom, I. J. Cox, M. L. Miller, and Y. M. Lui, “Rotation, scale, and translation-resilient public watermarking for images,” SPIE, pp. 90–98, January 2000. [6] M. Alghoniemy and A. H. Tewfik, “Geometric distortion correction through image normalization,” IEEE International Conference on Multimedia and Expo, pp. 1291–1294, August 2000. distortions,” IEEE International Conference on Image Processing, pp. 999-1002, October 2001. [10] G. Doerr, C. Rey, and J.-L. Dugelay, “Watermark resynchronization based on elastic graph matching,” the International Conference on Sciences of Electronic Technologies of Information and Telecommunications, March 2005. [11] J.L. Dugelay,S. Roche,C. Rey, G. Dorr, “Still image watermarking robust to local geometric distortions,” IEEE transactions on image processing, pp. 2831-2842, 2006. [12] P. Bas, J.-M. Chassery, and B. Macq, “Geometrically invariant watermarking using feature points,” IEEE Transactions on Image Processing, pp. 1014–1028, September 2002. [13] F. Dehuillaume, S. Voloshynovskiy, and T. Pun, “A method for the estimation and recovering from general affine transforms in digital watermarking applications,” SPIE, pp. 313–322, January 2002. [14] M. Awrangjeb, M. Murshed, and G. Lu, “Global geometric distortion correction in images,” IEEE Workshop on Multimedia Signal Processing, pp. 435-440, September 2006. [15] M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, “Image coding using wavelet transform,” IEEE Transactions on Image Processing, pp. 205-220, April 1992. [16] C.R. Huang, C.S. Chen, P.C. Chung, “Contrast context histogram-A discriminating local descriptor for image matching,” IEEE International Conference on Pattern Recognition, pp. 53–56, 2006. [17] T. Lindeberg, “Feature detection with automatic scale selection,” International Journal of Computer Vision, pp. 79–116, 1998. [18] D. Heckerman, “A tutorial on learning with bayesian networks,” Technical Report MSR-TR-95-06, 1995. [19] Fabien A. P. Petitcolas, Ross J. Anderson, Markus G. Kuhn, “Attacks on copyright marking systems,” Information Hiding, Second International Workshop, pp. 219-239, April 1998. [20] Shelby Pereira, Sviatoslav Voloshynovskiy, Maribel Madueno, Stephane Marchand-Maillet and Thierry Pun, “Second generation benchmarking and application oriented evaluation,” Information Hiding Workshop III, , April 2001. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44279 | - |
| dc.description.abstract | 本論文提出了一種新的浮水印技術能使用在回復幾何變形影像與攜帶資訊。
在我們的浮水印技術中，許多樣板會被藏在小波轉換域中。這些樣板能提供回復 幾何變形影像時所需的參考資訊。我們提出了一個演算法能在幾何變形的影像中 找出樣板的位置與所藏的資訊，值得注意的是我們的演算法並不需要原始圖片的 支援。此演算法是建構在貝氏網路的架構上。在幾何變形影像中樣板的位置和所 藏的資訊能夠以機率的方式表示在貝氏網路中。藉由推論貝式網路，樣板的位置 和所藏的資訊可以被估測出來。估測出樣板的位置後，樣板的位移就得以被計算 出來。接著再使用差補法估測出每個像素的位移，如此一來便能藉由這些資訊將 幾何變形影像回復。實驗的結果顯示出我們的浮水印技術能很強健的對抗幾何變 形，並且將幾何變形影像復原。 | zh_TW |
| dc.description.abstract | A novel watermarking scheme which recovers an image from geometric distortion
and carries multi-bit binary message is proposed in this thesis. In our watermarking scheme, several templates are inserted into the discrete wavelet transform domain and serves as the registration references. We provide a blind watermarking extraction algorithm to extract the hidden message and locate the templates. The locations of templates and binary message are represented probabilistically in the Bayesian network. The displacement parameters of each template can further be obtained once the locations of the templates are estimated. The distorted image is recovered based on the displacements of each pixel which is estimated by interpolation. Experiments demonstrate that proposed watermarking scheme are robust to local geometric distortion and is capable of recovering distorted images well. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T02:48:40Z (GMT). No. of bitstreams: 1 ntu-98-R96922093-1.pdf: 8462281 bytes, checksum: e845eb53622045e24615b686637e87ac (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi Chapter 1 Introduction 1 1.1 Image Recovery 2 1.2 Data Hiding 3 1.3 Paper Organization 4 Chapter 2 Related Work 4 2.1 Geometric Distortion Correction 5 2.2 Geometric Distortion Invariance Watermarking 5 2.2.1 Exhaustive Search 5 2.2.2 Image Registration 5 2.2.3 Geometric Distortion Invariance Domain 6 2.2.4 Method using a Template or a periodic watermark 6 2.2.5 Using Feature Point of the Image 7 Chapter 3 Background 8 3.1 Geometric distortion 10 3.1.1 Global geometric transformation 10 3.1.2 Local Geometric Transformation 12 3.2 Discrete Wavelet Transform 12 3.3 Contrast Context Histogram 14 3.4 Blob Detection 16 Chapter 4 Methodology 18 4.1 Overview 18 4.2 Watermarking Embedding 19 4.3 Watermarking Extraction 22 4.3.1 Similarity Measurement Model 24 4.3.2 Neighbor Relationship Model 25 4.3.3 The Procedure of Watermarking Extraction 26 4.4 Image recovery 28 Chapter 5 Experimental Result 29 5.1 Image Recovery 30 5.2 Data Hiding 33 5.2.1 Capacity 34 5.2.2 Fidelity 35 5.2.3 Robustness 36 Chapter 6 Conclusion 43 REFERENCE 44 | |
| dc.language.iso | en | |
| dc.title | 使用多位元浮水印回復幾何變形影像 | zh_TW |
| dc.title | Image Recovery of Geometric Distortion Using Multi-bit
Watermarking | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 吳家麟,郭天穎,葉家宏 | |
| dc.subject.keyword | 局部幾何變形,盲目偵測,數位浮水印,資訊隱藏,幾何變形回復, | zh_TW |
| dc.subject.keyword | Local geometric distortion,blind detection,digital watermarking,data hidden,geometric distortion correction, | en |
| dc.relation.page | 47 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-08-06 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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|---|---|---|---|
| ntu-98-1.pdf 目前未授權公開取用 | 8.26 MB | Adobe PDF |
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