在許多影像浮水印的研究中，大部分的方法在取出隱藏資料時都需要參考原影像，然而不需參考原影像方法的robust又不是很理想。因此在這篇論文中，主要是要提出一個不需要使用原影像就能夠將隱藏的資料取回的方法，而且再經過別人的攻擊之後，隱藏資料的存活率也能夠很高。

在這個方法中，我們利用DCT將能量集中的特性，將每個blocks的能量收集處理。隱藏資料時，先收集blocks經由DCT轉換後的DC係數，再利用這些DC係數除以某除數所得之餘數，藉由調整這些餘數的值使得調整後餘數的相對位置關係為其對應的隱藏資料。最後再利用一些常見的浮水印攻擊法來測試方法的強韌性（robust）。

在與相關演算法的結果比較之後，除了filter攻擊較差之外，其他攻擊後的誤差率都要來的小或是相差不多。因此我們所提出的方法除了不需使用原影像之外，強韌性也有很好的表現。而且可以根據要求的不同來調整參數，提供了很好的彈性調整，連影像品質最差的JPEG壓縮攻擊法的錯誤率，都可調整到少於1%。

Many existing researches on image watermarking for copyright protection need to use original image in retrieving watermark. Though it is more robust, it would cause some problems about the authorization of original image. In this thesis, we propose a method based on DCT domain without using original image. Using the property of concentrating energy in DCT transform, the energies of blocks are used for further processing. In the embedding algorithm, the DC coefficients of blocks are first collected. Then they are divided by some number to get remainders. The values of embedded data are embedded in the relationship between corresponding location of embedded data and other locations by adjusting the remainders in all locations.

Some typical watermarking attacks and noise are used to evaluate the robustness of our method. Compared with other competing algorithms, it shows that the survival rate of watermark in our method can be almost the same or even better then those methods which need original image. The error rate of the lowest quality JPEG compression can be adjusted less then 1%, when the length of embedding data is 512 bits. Our proposed method can be further improved by adjusting the values of remainders and the block size. These provide flexibility to satisfy different requirements.

1. 簡介
2. 相關文獻探討
3. 研究方法
3.1 DCT的介紹
3.2 隱藏浮水印演算法
3.3 取回浮水印演算法
4. 實驗參數對於誤差率之影響
4.1 實驗評估方法
4.2 區塊大小對於誤差率之影響
4.3 除數大小對於誤差率之影響
5. 實驗與討論
5.1 JPEG compression
5.2 Noise
5.3 Rescaling
5.4 Filter
5.5 Cropping
5.6 Brightness
6. 結論
參考文獻

[1] Mitchell D. Swanson,Mei Kobayashi and Ahmed H. Tewfik, “Multimedia Data-Embedding and Watermarking Technologies,” Proceedings of the IEEE, Vol. 86, No. 6, June 1998

[2] Raymond B. Wolfgang, and Christine I. Podilchuk, “Perceptual Watermarks for Digital Images and Video,” Proceedings of the IEEE, Vol. 87, No. 7, pp. 1108-1126, 1999

[3] Mitchell D. Swanson, Bin Zhu, and Ahmed H. Tewfik, “Multiresolution Scene-Based Video Watermarking Using Perceptual Models,” IEEE Journal on Selected Areas in Communications, Vol. 16, No. 4, pp. 540-550, 1998

[4] Tae-Yun Chung, Min-Suk Hong, Young-Nam Oh, Dong-Ho Shin, and Sang-Hui Park, “Digital Watermarking for Copyright Protection of MPEG2 Compressed Video,” IEEE Transactions on Consumer Electronics, Vol. 44, No. 3, pp. 895-901, 1998

[5] Jiwu Huang, and Yun Q. Shi, “Adaptive Image Watermarking Scheme based on Visual Masking,” IEE Electronics Letters, Vol. 34, No. 8, pp.748-750,1998

[6] Ryutarou Ohbuchi, Hiroshi Masuda, and Masaki Aono, “Watermarking Three-Dimensional Polygonal Models Through Geometric and Topological Modifications,” IEEE Journal on Selected Areas in Communications, Vol. 16, No. 4, pp. 551-559, 1998

[7] S. Craver, N. Memon, B.-L. Yeo, and M. M. Yeung, “Resolving Rightful Ownerships with Invisible Watermarking Techniques: Limitations, Attacks, and Implications,” IEEE Journal on Selected Areas in Communications, Vol. 16, No. 4, pp. 573-586, 1998

[8] Z. H. Wei, P. Qin, and Y. Q. Fu, “Perceptual Digital Watermark of Images Using Wavelet Transform,” IEEE Transactions on Consumer Electronics, Vol. 44, No. 4, pp. 1267-1272,1998

[9] Wenjun Zeng, and Bede Liu, “A Statistical Watermark Detection Technique Without Using Original Image for Resolving Rightful Ownerships of Digital Images,” IEEE Transactions on Image Processing, Vol. 8, No. 11, pp. 1534-1548, 1999

[10] Mohan S Kankanhalli, Rajmohan, and K R Ramakrishnan, “Adaptive Visible Watermarking of Images,” Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Vol. 1, pp.568-573, 1999

[11] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, “Secure Spread Spectrum Watermarking for Multimedia,” IEEE Trans. Image Processing, Vol. 6, No. 12, pp. 1673-1687, Dec. 1997

[12] Christine I. Podilchuk, and Wenjun Zeng, “Image-Adaptive Watermarking Using Visual Models,” IEEE Journal on Selected Areas in Communications, Vol. 16, No. 4, pp. 525-539, 1998

[13] Wen-Nung Liw, Chih-Liang Wu, and Guo-Shiang Lin, “Robust Image Watermarking On the DCT Domain,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 9-15, 1999

[14] Wen-Nung Liw, and Li-Chun Chang, “Spatial-Domain Image Watermarking By Data Embedding At Adaptive Bit Positions,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 16-21, 1999

[15] Hen-Ming Chang, and Ling-Hwei Chen, “An Invisible Watermarking Method for Color Image,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 22-29, 1999

[16] Hong-Yuan Mark Liao, Chun-Shien Lu, Shih-Kun Huang, and Chwen-Jye Sze, “Cocktail Watermarking on Images and Audios,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 30-37, 1999

[17] Da-Chu Wu, and Wen-Hsiang Tsai, ”An Efficient Method for Imperceptive Data Embedding in Images,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 166-173, 1999

[18] Soo-Chang Pei, Yu-Hau Chen, and Tu-Fang Torng, “Digital Image and Watermarking Utilizing Just-Noticeable-Distortion Model,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 174-182, 1999

[19] Wen-Chu Cheng, Ching-Wen Chu, and Jia-Shung Wang, “A Robust watermarking Method on Discrete Cosine Transform Domain,” 1999 12th IPPR Conference on Computer Vision, Graphics and Image Processing, pp. 191-198, 1999