臺灣博碩士論文加值系統

所謂數位浮水印是將位元串組成的序列資料，加入數位訊號（例如影像）中並用於識別資料的版權或所有權資訊。相較於需要參考原始資料的非盲目型浮水印，本論文提出的數位浮水印技術均屬於盲目型，也就是抽取浮水印時無需參考原始影像或其相關資訊。
我們首先提出一種創新的密文隱藏技術，藉由冗餘離散小波轉換，將密文隱藏於彩色掩護影像的飽和度次頻帶成分中，同時藉由直接飽和度調整技術保留了掩護影像的強度與色度，抽取隱藏密文則不需原始影像的協助，可直接透過獨立成分分析技術從掩護影像中分離出來。第二項研究為具備修改區域偵測及所有權宣告雙重功能的遙測影像網頁浮水印機制，配合浮水印預設強度以及每個影像圖塊本身的統計資訊，結合離散小波轉換以調適性方式將多組浮水印藏入遙測影像中，同時能夠大幅減輕密鑰存管問題。第三項研究亦屬於盲目數位浮水印，結合尺度不變特徵轉換以及離散小波轉換，以調適性方式於特定區塊藏入浮水印，並能抵抗旋轉以及一般的壓縮攻擊。
由於行動通訊與雲端科技已成為資訊應用主流，本研究後續將嘗試與圖形運算單元結合，以雲端運算方式以達成近即時的浮水印加解密計算，並搭配行動裝置的基本運算能力進行浮水印驗證。

A digital watermark is a pattern of bits inserted into a digital signal such as image file, that identifies the data's copyright or ownership information. Comparing with the traditional non-blind watermarking schemes, the proposed digital watermark schemes in this dissertation are all blind, which means that they require neither the original imagery nor any side information in the watermark recovery procedure.
Firstly, we present a novel secret text hiding technique, where the secret text is embedded into the low frequency sub-band of the saturation component of a color image via redundant discrete wavelet transform (RDWT), while the color image's intensity and hue components are preserved with direct saturation adjustment, and the hidden secret text can be extracted from the watermarked image based on independent component analysis (ICA) without referring to the original cover image. The next one we proposed is a remote-sensing imagery web watermarking scheme, which equipped with dual functions of temper detection and ownership declaration. With the pre-defined watermark strength and statistical information of every image tile, not only multiple watermarks can be adaptive embedded into image tiles utilizing the discrete wavelet transform (DWT), but also significantly reduce the secret keys depository problems. The third scheme is alos a blind digital watermark, by utilize the scale-invariant feature transform (SIFT) and discrete wavelet transform, the watermarks can be adaptive embedded into selected blocks and to resist rotation and common compression attacks.
In view of the mobile telecommunications and cloud applications have become the mainstream of information applications, we planning to integrate graphic procssing units (GPUs) and watermarking scheme, via cloud computing to fulfill the requirement of near real-time watermark encryption and decryption, and utilize the basic computing power of mobile devices in the watermark verification.

誌謝 ii
摘要 iii
ABSTRACT iv
目錄 vi
表目錄 ix
圖目錄 x
1. 緒論 1
1.1 研究背景 1
1.2 研究動機 1
1.3 研究方向與目的 3
1.4 論文架構 3
2. 數位浮水印技術 4
2.1 浮水印的歷史 4
2.2 數位浮水印系統簡介 4
2.3 數位浮水印攻擊技術分析 9
2.4 彩色數位浮水印技術 11
3. 結合獨立成分分析的數位浮水印方法 13
3.1 前言 13
3.2 小波轉換 13
3.3 冗餘離散小波轉換 19
3.4 飽和度調整 22
3.4.1 RGB色彩模型 22
3.4.2 彩色模型轉換與飽和度調整技術 23
3.5 獨立成分分析 26
3.6 浮水印加密程序 29
3.6.1 無色影像的獲得與浮水印攪亂 29
3.6.2 浮水印適應性攪亂 31
3.6.3 在空間域修改無色成分的LL2頻帶像素數值 32
3.6.4 運用飽合度調整將浮水印嵌入彩色影像 32
3.7 浮水印萃取程序 33
3.7.1 組合出三組成分 34
3.7.2 快速獨立成分分析進行處理 36
3.7.3 浮水印相似度量測 38
3.8 實驗結果 39
3.9 小結 46
4. 結合離散小波轉換的數位浮水印方法 48
4.1 前言 48
4.2 浮水印加密程序 50
4.2.1 取出原始彩色影像的無色成分 50
4.2.2 選取浮水印影像及攪亂 50
4.2.3 子頻帶HL與LH差值統計特性與量化門檻計算 51
4.2.4 配合量化門檻值藏入浮水印 51
4.3 浮水印解密程序 53
4.3.1 幾何修正及取出彩色影像無色成分 53
4.3.2 子頻帶HL與LH差值計算 55
4.3.3 浮水印還原 55
4.4 實驗結果 56
4.5 小結 71
5. 結合抗幾何攻擊的數位浮水印方法 73
5.1 前言 73
5.2 抗幾何攻擊浮水印演算法 74
5.3 尺度不變特徵轉換 77
5.4 浮水印加密程序 80
5.4.1 取出原始彩色影像的無色成分 80
5.4.2 特徵點選擇 81
5.4.3 浮水印攪亂 82
5.4.4 子頻帶差值統計特性與量化門檻計算 83
5.4.5 配合量化門檻值藏入浮水印 83
5.5 浮水印解密程序 84
5.5.1 無色成分與特徵點選擇 84
5.5.2 子頻帶差值計算 84
5.5.3 浮水印還原 84
5.6 實驗結果 85
5.6.1 浮水印隱藏於第2階DWT係數之旋轉攻擊測試 85
5.6.2 浮水印隱藏於第2階及第3階DWT係數之攻擊結果比較 86
5.6.3 量化門檻乘數對於浮水印抽取效果之影響比較 93
5.7 小結 95
6. 結論與未來研究方向 97
6.1 結論 97
6.2 未來應用與研究方向 98
參考文獻 99
論文發表 105
自傳 106

[1]http://www.tipo.gov.tw/ch/AllInOne_Show.aspx?path=2383&guid=55f0b0ff-4c37-41af-9574-1e60a08c7144&lang=zh-tw (2013.03.15)
[2]張真誠，“淺談數位浮水印”，暨大電子雜誌科技類，第16期，第1-4頁，2002。
[3]Meggs, P. B., A History of Graphic Design, 3rd Ed., John Wiley & Sons, p. 58, 1998.
[4]http://maps.google.com.tw/intl/zh-TW/help/maps/streetview/ (2013.02.27)
[5]http://www.currency.cbc.gov.tw/tb6.htm (2013.02.27)
[6]Artz, D., “Digital Steganography: Hiding Data Within Data,” IEEE Internet Computing, Vol. 5, No. 3, pp. 75-80, 2001.
[7]蔡坤龍，“基於碎形正交基底之資訊隱藏技術”，碩士論文，中山大學資訊工程學系，第3-4頁，2005。
[8]蕭人豪、林欣慧、林金龍、林麗虹，“數位浮水印技術發展現況：以數位典藏計畫為例”，第三屆數位典藏技術研討會，臺北市，第1-6頁，2004。
[9]Su, J. K., Hartung, F., and Girod, B., “Digital Watermarking of Text, Image, and Video Documents, ” Computers & Graphics, Vol. 22, No. 6, pp. 687-695, 1998.
[10]Cox, I. J. and Miller, M. L., “The First 50 Years of Electronic Watermarking,” Journal of Applied Signal Processing, Vol. 2002, No. 2, pp. 126-132, 2002.
[11]Cox, I., Miller, M., Bloom, J., Fridrich, J., and Kalker, T., Digital Watermarking and Steganography, 2nd Ed., Morgan Kaufmann, pp. 325-332, 2008.
[12]Song, C., Sudirman, S., and Merabti, M., “A Spatial and Frequency Domain Analysis of the Effect of Removal Attacks on Digital Image Watermarks,” Proceedings of 11th PGNet, Liverpool, UK, pp. 119-124, 2010.
[13]Hussein, J. A., “Spatial Domain Watermarking Scheme for Colored Images Based on Log-Average Luminance,” Journal of Computing, Vol. 2, No. 1, pp. 100-103, 2010.
[14]Kutter, M., “Watermarking Resisting to Translation, Rotation, and Scaling,” Proceedings of SPIE 3528, Multimedia Systems and Applications, pp. 423-431, 1999.
[15]Ahmidi, N. and Safabakhsh, R., “A Novel DCT-Based Approach for Secure Color Image Watermarking,” Proceedings of ITCC 2004 International Conference, Las Vegas, USA, Vol. 2, pp. 709-713, 2004.
[16]Chang, C. P., Lee, Y. C., Chang, A. C., Huang, P. S., and Tu, T. M., “StarMarker-A Fast and Robust RGB-Based Saturation Watermarking System for Pan-Sharpened IKONOS and QuickBird Imagery,” Optical Engineering, Vol. 45, No. 5, pp. 056202-056202, 2006.
[17]Chou, C. H. and Wu, T. L., “Embedding Color Watermarks in Color Images,” EURASIP Journal on Applied Signal Processing, Vol. 1, pp. 32-40, 2003.
[18]Mallat, S., A Wavelet Tour of Signal Processing, Academic Press, USA, pp. 79-89, 1998.
[19]Daubechies, I., Ten Lectures on Wavelets, Society for Industrial and Applied Mathematics, Philadelphia, USA, Vol. 61, pp. 1-16, 1992.
[20]Hua, L. and Fowler, J. E., “RDWT and Image Watermarking,” Technical Report MSSU-COE-ERC-01, Engineering Research Center of Mississippi State University, USA, Vol. 18, pp. 1-21, 2001.
[21]Cox, I. J., Kilian, J., Leighton, F. T., and Shamoon, T., “Secure Spread Spectrum Watermarking for Multimedia,” IEEE Transactions on Image Processing, Vol. 6, No. 12, pp. 1673-1687, 1997.
[22]Huang, J., Shi, Y. Q., and Shi, Y., “Embedding Image Watermarks in DC Components,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 10, No. 6, pp. 974-979, 2000.
[23]Huang, P. S., Chiang, C. S., Chang, C. P., and Tu, T. M., “Robust Spatial Watermarking Technique for Colour Images via Direct Saturation Adjustment,” Vision, Image and Signal Processing, IEE Proceedings, Vol. 152, No. 5, pp. 561-574, 2005.
[24]Gonzalez, R. C. and Woods, R. E., Digital Image Processing, 2nd Ed., Prentice Hall, pp. 299-231, 2002.
[25]Kermit, M. and Tomic, O., “Independent Component Analysis Applied on Gas Sensor Array Measurement Data,” IEEE Sensors Journal, Vol. 3, No. 2, pp. 218-228, 2003.
[26]Hien, T. D., Nakao, Z., and Chen, Y. W., “Robust RDWT-ICA Based Information Hiding,” Soft Computing, Vol. 10, No. 12, pp. 1135-1144, 2006.
[27]Hsu, C. T. and Wu, J. L., “Hidden Digital Watermarks in Images,” IEEE Transactions on Image Processing, Vol. 8, No. 1, pp. 58-68, 1999.
[28]Yu, D. and Sattar, F., “A New Blind Watermarking Technique Based on Independent Component Analysis,” Digital Watermarking, pp. 51-63, 2003.
[29]Petitcolas, F. A. P., Anderson, R. J., and Kuhn, M. G., “Attacks on Copyright Marking Systems,” in Information Hiding, Second International Workshop, Portland, USA, pp. 218-238, 1998.
[30]Petitcolas, F. A. P., “Watermarking Schemes Evaluation,” IEEE Signal Processing, Vol. 17, No. 5, pp. 58-64, 2000.
[31]Adams M. D. and Kossentini, F., “JasPer: A Software-Based JPEG-2000 Codec Implementation,” Proceedings of International Conference on Image Processing, Vancouver, Canada, Vol. 2, pp.53-56, 2000.
[32]http://www.xnview.com/ (2013.3.17)
[33]http://maps.google.com/ (2013.3.8)
[34]http://www.bing.com/maps/ (2013.3.18)
[35]http://maps.yahoo.com/ (2013.3.18)
[36]http://www.urmap.com/ (2013.3.18)
[37]http://gis.rchss.sinica.edu.tw/google/?p=2056 (2013.3.18)
[38]謝銘洋、趙義隆、陳曉慧，“數位典藏之保護與授權加值應用相關法律問題探討”，藝術教育研究，第16期，第77-106頁，2008。
[39]Kitanovski, V., Taskovski, D., and Bogdanova, S., “Watermark Generation Using Image-Dependent Key for Image Authentication,” in EUROCON 2005, the International Conference on “Computer as a Tool", Serbia & Montenegro, Belgrade, pp. 947-950, 2005.
[40]http://geospatial.intergraph.com/products/ERDASIMAGINE/ERDASIMAGINE/Details.aspx (2013.3.18)
[41]http://geospatial.intergraph.com/products/ERDASIMAGINE/IMAGINEAutoSync/Details.aspx (2013.3.18)
[42]Lowe, D. G., “Distinctive Image Features from Scale-Invariant Keypoints,” International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004.
[43]Bay, H., Tuytelaars. T., and Van Gool, L., “SURF: Speeded Up Robust Features,” Proceedings of Computer Vision-ECCV 2006, Graz, Austria, pp. 404-417, 2006.
[44]Verstrepen, L., Meesters, T., Dams, T., Dooms, A., and Bardyn, D., “Circular Spatial Improved Watermark Embedding Using a New Global SIFT Synchronization Scheme,” IEEE 16th International Conference on Digital Signal Processing, pp. 1-8, 2009.
[45]Liu, K. C. and Chou, C. H., “Robust and Transparent Watermarking Scheme for Colour Images,” IET Image Processing, Vol. 3, No. 4, pp. 228-242, 2009.
[46]Lee, H. Y., Kim, H., and Lee, H. K., “Robust Image Watermarking Using Local Invariant Features,” Optical Engineering, Vol. 45, No. 3, pp. 037002-037002, 2006.
[47]Su, P. C. and Chang, Y. C., “A Geometrically Resilient Digital Image Watermarking Scheme Based on SIFT and Extended Template Embedding,” Proceedings of INTERNET 2012, The Fourth International Conference on Evolving Internet, Venice, Italy, pp.102-107, 2012.
[48]Nasir, I., Khelifi, F., Jiang, J., and Ipson, S., “Robust Image Watermarking via Geometrically Invariant Feature Points and Image Normalization,” Image Processing, IET, Vol. 6, No. 4, pp. 354-363, 2012.
[49]Shen, Z. W. and Wu, J. T., “Geometrically Invariant Watermarking Based on Nonlinear Anisotropic Diffusion,” 2011 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), Guilin, Guangxi, pp. 126-131, 2011.
[50]Lin, C. Y., Wu, M., Bloom, J. A., Cox, I. J., Miller, M. L., and Lui, Y. M., “Rotation, Scale, and Translation Resilient Watermarking for Images,” IEEE Transactions on Image Processing, Vol. 10, No. 5, pp. 767-782, 2001.
[51]Kim, H. S. and Lee, H. K., “Invariant Image Watermarking Using Zernike Moments,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, No. 8, pp. 766-775, 2003.
[52]Xiang, S., Kim, H. J., and Huang, J., “Invariant Image Watermarking Based on Statistical Features in Low-Frequency Domain,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 18, No. 6, pp. 777-790, 2008.
[53]Sun, J. G. and He, W., “RST Invariant Watermarking Scheme Based on SIFT Feature and Pseudo-Zernike Moment,” 2nd International Symposium on Computational Intelligence and Design, Hangzhou, Zhejiang, 2010.
[54]Luo, H., Sun, X., Yang, H., and Xia, Z., “A Robust Image Watermarking Based on Image Restoration Using SIFT,” Radioengineering, Vol. 20, No. 2, pp. 525-532, 2011.
[55]Lowe, D. G., “Object Recognition From Local Scale-Invariant Features,” Proceedings of the Seventh IEEE International Conference on Computer Vision, Corfu, Greece, pp. 1150-1157, 1999.
[56]Brown, M. and Lowe, D. G., “Automatic Panoramic Image Stitching Using Invariant Features,” International Journal of Computer Vision, Vol. 74, No. 1, pp. 59-73, 2006.
[57]Wagner, D., Schmalstieg, D., and Bischof, H., “Multiple Target Detection and Tracking with Guaranteed Frame Rates on Mobile Phones,” 8th IEEE International Symposium on Mixed and Augmented Reality, Orlando, USA, pp. 57-64, 2009.
[58]Scovanner, P., Ali, S., and Shah, M., “A 3-Dimensional SIFT Descriptor and Its Application to Action Recognition,” 15th International Conference on Multimedia, Augsburg, Germany, pp. 357-360, 2007.
[59]Koenderink, J. J., “The Structure of Images,” Biological Cybernetics, Vol. 50, No. 5, pp. 363-396, 1984.
[60]Lindeberg, T., “Scale-Space Theory: A Basic Tool for Analysing Structures at Different Scales,” Journal of Applied Statistics, Vol. 21, No. 2, pp. 225-270, 1994.
[61]Juan, L. and Gwun, O., “A Comparison of SIFT, PCA-SIFT and SURF,” International Journal of Image Processing, Vol. 3, No. 4, pp. 143-152, 2009.