| 研究生: |
周子捷 Chou, Tzu-Chieh |
|---|---|
| 論文名稱: |
基於離散小波轉換抵抗影像幾何失真攻擊之強韌型浮水印技術 DWT Based Robust Watermarking Technique for Against Geometric Attacks |
| 指導教授: |
王明習
Wang, Ming-Shi |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 工程科學系 Department of Engineering Science |
| 論文出版年: | 2011 |
| 畢業學年度: | 99 |
| 語文別: | 中文 |
| 論文頁數: | 78 |
| 中文關鍵詞: | 數位浮水印 、離散小波轉換 、幾何失真 、特徵擷取 |
| 外文關鍵詞: | Digital Watermarking, Discrete Wavelet Transform (DWT), Geometric Distortion, Feature Extraction |
| 相關次數: | 點閱:92 下載:1 |
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隨著電腦科技的持續進步,數位影像在生活中的應用也逐漸增加,數位影像版權的保護也越來越受到重視。數位浮水印技術是目前針對數位影像或者數位影片的版權保護而廣為使用的技術。然而,當資料受到轉換或攻擊時,如何保護浮水印不受到破壞仍然是現今浮水印技術重要的議題。因此,本篇論文提供了一個基於影像特徵與離散小波轉換的數位影像浮水印技術,它能有效抵抗影像的旋轉與縮放等影像幾何失真的攻擊。首先,原始影像經由離散小波轉換後,將指定的浮水印嵌入至其中的中頻區域,同時我們利用Harris演算法將小波轉換後低頻的特徵點擷取出來,並且利用了整張影像的高頻強度,將不同影像的特徵點數量控制在一定的範圍內,最後將另一浮水印嵌入至特徵點當中。若目標影像遭受到旋轉或者縮放攻擊時,利用影像特徵點不變的特性,我們可以利用嵌入特徵點的浮水印計算出中頻區域浮水印的位置並將之取出。為了檢查浮水印系統的強韌性,我們測試了影像不同角度的旋轉以及不同倍率的縮放並且加上了一般常見的浮水印攻擊手段如加入高斯雜訊、JPEG壓縮及影像裁剪。實驗結果顯示在這些測試之下浮水印依然有著良好的強韌性,達到了強韌型浮水印系統的優良效果。
As the applications of digital images become much common in our lives, protection of digital images’ content or copyright is more emphasized. Digital watermarking is a well-known technology that usually embedded a specific watermark on the image. However, it is still a challenged issue for finding any proper algorithm which can against variant image processing operations or attacks to the watermarked image. In this thesis, a robust digital image watermarking technology based on image feature points and wavelet transformation was proposed. The proposed watermarking method provided effectively the capability of resisting geometric distortion of images such as rotation and scaling. Firstly, the image is decomposed into four subbands by Haar wavelet transform. A specified watermark is embedded on the middle frequency band. At the same time, the image is divided into blocks and done the wavelet transform for each block. The feature points of each block are extracted from the transformed low frequency band by Harris’ method. The transformed high frequency band is used to evaluate of the number of feature points must be kept for the corresponding block. The locations of these feature points and the number of features for each block is composed as the second watermark and to be embedded. To examine the robustness of the proposed method for geometric distortions and attacks, the combination of various rotation angles, scaling factors, and image processing operations such as JPEG, noising, copy-and-paste of the watermarked image have been tested. The experimental results show that the proposed method is very encouraged.
[1] Ambalanath Shan and Ezzatollah Salari, "REAL-TIME DIGITAL VIDEO WATERMARKING," IEEE International Conference on Consumer Electronics,, pp.12-13, 2002.
[2] Eugene T. Lin and Edward J. Delp, “A Review of Fragile Image Watermarks,” CERIAS Tech Report 2001-74, 1999.
[3] Sanjay Rawat and Balasubramanian Raman , “A chaotic system based fragile watermarking scheme for image tamper detection,” AEU - International Journal of Electronics and Communications, Article in Press, 2011.
[4] Tien-You Lee and Shinfeng D. Lin, “Dual watermark for image tamper detection and recovery,” Pattern Recognition, Vol.41, No.11, pp.3497-3506, 2008.
[5] Chun-Wei Yang and Jau-Ji Shen, “Recover the tampered image based on VQ indexing,” Signal Processing, Vol.90, No.1, pp.331-343, 2010.
[6] Mauro Barni, Franco Bartolini, Vito Cappellini, and Alessandro Piva, “A DCT-domain system for robust image watermarking,” Signal Processing, Vol.66, No.3, pp.357-372, 1998.
[7] Vassilios Solachidis and Ioannis Pitas, “Circularly Symmetric Watermark Embedding in 2-D DFT Domain,” IEEE Transactions on Image Processing, Vol.10, No.11, pp. 1741-1753, Nov. 2001.
[8] V. Licks and R. Jordan, “On Digital Image Watermarking Robust To Geometric Transformations,” IEEE International Conference on Image Processing, Vol.3, pp.690-693, 2000.
[9] Amani Bin Sewaif, Mohammed Al-Mualla ,and Hussain AI-Ahmad, “2-D Walsh Coding for Robust Digital Image Watermarking,” IEEE International Symposium on Signal Processing and Information Technology, pp.302-305, Dec. 2004.
[10] Deepa Kundur, Dimitrios Hatzinakos, “A Robust Digital Image Watermarking Method using Wavelet-Based Fusion,” IEEE International Conference on Image Processing, Vol.1, pp.544-547, Oct. 1997.
[11] Young-Sik Kim, O-Hyung Kwon ,and Rae-Hong Park , “Wavelet based watermarking method for digital images using the human visual system,” Electronics Letters,Vol.35 No.6, pp.466-468, March 1999.
[12] Mary Anaculate and Aloysius George, “A Novel and Robust Approach for Digital Watermarking Using Lifting Wavelet Transform,” American Journal of Scientific Research, Vol.12, No.13, pp.118-130, 2011.
[13] Min-Jen Tsai, Kuang-Yao Yu, and Yi-Zhang Chen, “Wavelet Packet and Adaptive Spatial Transformation of Watermark for Digital Image Authentication,” IEEE International Conference on Image Processing,pp.450-453, 2000.
[14] Ikpyo Hong, Intaek Kim, and Seung-Soo Han, “A Blind Watermarking Technique Using Wavelet Transform,” IEEE International Symposium on Industrial Electronics, Vol. 3, pp.1946-1950, Jun 2001.
[15] Mauro Barni, Franco Bartolini, and Alessandro Piva , “Improved Wavelet-Based Watermarking Through Pixel-Wise Masking,” IEEE Transactions on Image Processing, Vol. 10, No. 5, pp.783-791, May 2001
[16] Xiu-mei Wen, Wei Zhao, and Fan-xing Meng, “Research of a Digital Image Watermarking Algorithm Resisting Geometrical Attacks in Fourier Domain,” International Conference on Computational Intelligence and Security, pp.265-268, 2009.
[17] Xiaoli Zhang and Xin Lv, “A Novel Watermarking Algorithm Resist to Geometrical Attacks,” International Conference on Electronic Commerce and Business Intelligence, pp.503-506, 2009.
[18] I. J. Cox, M. L. Miller, and J. A. Bloob, “Digital Watermarking,” Morgan Kaufmann Publishers, Second Edition, Printed in the USA, 2008.
[19] Ping Dong and Nikolas P. Galatsanos, “Affine Transformation Resistant Watermarking Based on Image Normalization,” IEEE International Conference on Image Processing,” Vol. 3, pp.489-492, June 2002.
[20] Masoud Alghoniemy and Ahmed H. Tewfik, “Geometric Distortion Correction Through Image Normalization,” IEEE International Conference on Multimedia and Expo, Vol. 3, pp.1291-1294, Aug. 2002.
[21] Li Li, He-Huan Xu, Chin-Chen Chang and Ying-Ying Ma, “A novel image watermarking in redistributed invariant wavelet domain,” The Journal of Systems and Software, Vol. 84, No.6, pp.923-929, 2011.
[22] C.Harris and M. Stephens, “A Combined Corner and Edge Detector,” Proceedings of 4th Alvery Vision Conference, pp. 147-151, 1998.
[23] Li-pi Niu, Xiu-hua Jiang, Wen-hui Zhang, and Dong-xin Shi, “Image Registration Based on Hausdorff Distance,” IEEE International Conference on Networking and Information Technology, pp. 252-256, 2010.
[24] Marc Antonini, Michel Barlaud , Pierre Mathieu, and Ingrid Daubechies, “Image Coding Using Wavelet Transform,” IEEE Transactions On Image Processing, Vol. 1, No.2, APRIL 1992.
[25] H.P. Moravec, “Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover,” tech. report CMU-RI-TR-80-03, Robotics Institute, 1980.