利用特徵點偵測之強健型數位影像浮水印

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：20

、訪客IP：18.227.111.98

姓名

黃耀萱(Yao-hsuan Huang) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

利用特徵點偵測之強健型數位影像浮水印
(A Robust Image Watermarking Scheme based on Scale-Space Feature Point Detection)

相關論文

★ 基於QT之跨平台無線心率分析系統實現	★ 網路電話之額外訊息傳輸機制
★ 針對與運動比賽精彩畫面相關串場效果之偵測	★ 植基於向量量化之視訊/影像內容驗證技術
★ 植基於串場效果偵測與內容分析之棒球比賽精華擷取系統	★ 以視覺特徵擷取為基礎之影像視訊內容認證技術
★ 使用動態背景補償以偵測與追蹤移動監控畫面之前景物	★ 應用於H.264/AVC視訊內容認證之適應式數位浮水印
★ 棒球比賽精華片段擷取分類系統	★ 利用H.264/AVC特徵之多攝影機即時追蹤系統
★ 利用隱式型態模式之高速公路前車偵測機制	★ 基於時間域與空間域特徵擷取之影片複製偵測機制
★ 結合數位浮水印與興趣區域位元率控制之車行視訊編碼	★ 應用於數位智權管理之H.264/AVC視訊加解密暨數位浮水印機制
★ 基於文字與主播偵測之新聞視訊分析系統	★ 植基於數位浮水印之H.264/AVC視訊內容驗證機制

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

幾何變形攻擊，包括裁切、旋轉、尺度縮放，甚至隨機變形等，所產生的同步問題，對於數位影像浮水印的偵測影響極大。本研究提出了一種基於特徵點擷取之數位浮水印方法，來抵抗對於靜態圖片的幾何變形攻擊。首先，尺度不變之特徵點將會被擷取出來做為定位點，此特徵點亦能存活於一般的訊號處理以及仿射轉換等攻擊。利用此類特徵點適當的強韌性，我們依據特徵點位置建構出多個局部幾何不變之格狀形區域，並於每個局部幾何不變區域中嵌入兩種訊號，第一種為隱藏資訊之數位浮水印，以及第二種做為同步機制的訊號，此訊號又稱為樣板訊號。樣版訊號可以確保較大範圍之局部幾何不變區域能夠被擴張建構出來以提供經過幾何攻擊後之浮水印偵測。較大的偵測區域將使得浮水印嵌入量獲得提升，且浮水印的可信度也隨之增加。在偵測浮水印時，我們對於每個特徵點所定位之格狀區域參數進行微調整，尋找局部之最佳可能區域，浮水印訊號將因此被更可靠地偵測。實驗結果顯示我們所提出的浮水印方法對於幾何攻擊具有強健性，並且能夠抵抗一般的訊號處理攻擊。

摘要(英)

Geometrical transformations, such as cropping, rotation, scaling or even random bending, cause the synchronization problem of detecting the digital image watermark. This research presents a feature-based watermarking scheme to deal with geometrical attacks in still images. First, the scale-invariant feature extraction is applied to locate the interest points that can survive the signal processing
procedures and affine transforms. A local invariant region based on the scale-space features of an image is then acquired. At each invariant region, two signals will be embedded, {em i.e.} the watermark carrying the hidden information and the extended synchronization pattern or grid, which helps to ensure that a reasonably large invariant region be available for carrying the watermark payload and increasing the confidence of watermark
extraction. The detection of the grid is based on the local search by adjusting the related parameters of the grid to match with the possible hidden pattern so that the watermark can be retrieved afterwards. Experimental results demonstrate that the proposed scheme is robust against common image processing and geometrical
attacks.

關鍵字(中)

★ 數位浮水印
★ 幾何變形攻擊
★ 特徵點擷取

關鍵字(英)

★ digital watermarking
★ geometrical transformation
★ SIFT

論文目次

1 Introduction 1
1.1 Signi cance of the Research . . . . . . . . . . . . . . 1
1.2 Contribution of the Research . . . . . . . . . . . . . . 3
1.3 Thesis Organization . . . . . . . . . . . . . . . . . . . 4
2 Review of the Related Work 5
3 The Proposed Watermarking Scheme 10
3.1 Scale-Space Feature Points Extraction . . . . . . . . 11
3.2 Preprocessing . . . . . . . . . . . . . . . . . . . . . . 17
3.2.1 Invariant Region Generation . . . . . . . . . . 18
3.2.2 Key Points Elimination . . . . . . . . . . . . . 19
3.2.3 Embedding Regions Extending . . . . . . . . 22
3.3 Watermark Embedding . . . . . . . . . . . . . . . . . 25
3.4 Watermark Detection . . . . . . . . . . . . . . . . . . 30
4 Experimental Results 35
4.1 False Alarm Analysis . . . . . . . . . . . . . . . . . . 36
4.2 Fidelity Test . . . . . . . . . . . . . . . . . . . . . . . 37
4.3 Robustness Test . . . . . . . . . . . . . . . . . . . . . 37
5 Conclusion and Future Work 45

參考文獻

[1] F. Aurenhammer. Voronoi diagrams - a survey of a fundamental geometric data structure. ACM Computing Surveys (CSUR), 23(3):345-405, 1991.
[2] P. Bas, J.M. Chassery, and B. Macq. Geometrically invariant watermarking using feature points. IEEE Transactions on Image Processing, 11(9):1014-1028, 2002.
[3] I. Cox, M. Miller, and J. Bloom. Digital watermark: Principle and practice, 2001.
[4] X. Gao, C. Deng, X. Li, and D. Tao. Geometric Distortion Insensitive Image Watermarking in A ne Covariant Regions. IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews, 40(3):278-286, 2010.
[5] C. Harris and M. Stephens. A combined corner and edge detector. In Alvey vision conference, volume 15, page 50. Manchester, UK, 1988.
[6] A. Herrigel, S. Voloshynovskiy, and Y. Rytsar. The watermark template attack. In SPIE Security and Watermarking of Multi-media Contents III, volume 4314, pages 394-405. Citeseer, 2001.
[7] M. Kutter. Watermarking resisting to translation, rotation, and scaling. In SPIE The International Society for Optical Engineering, volume 3528, pages 423-431. Citeseer, 1999.
[8] M. Kutter, S.K. Bhattacharjee, and T. Ebrahimi. Towards second generation watermarking schemes. In IEEE International Confernece on Image Process, volume 1, pages 320-323, 1999.
[9] D.G. Lowe. Distinctive image features from scale-invariant key-points. International journal of computer vision, 60(2):91-110, 2004.
[10] B.S. Manjunath, C. Shekhar, and R. Chellappa. A new approach to image feature detection with applications. Pattern Recognition, 29(4):627-640, 1996.
[11] K. Mikolajczyk and C. Schmid. Scale & a ne invariant interest point detectors. International Journal of Computer Vision, 60(1):63-86, 2004.
[12] S. Pereira and T. Pun. Fast robust template matching for a neresistant image watermarks. In Information Hiding, pages 199-210. Springer, 1999.
[13] F.A.P. Petitcolas, M. Steinebach, F. Raynal, J. Dittmann,
C. Fontaine, and N. Fates. A public automated web-based evaluation service for watermarking schemes: StirMark benchmark. In SPIE proceedings series, pages 575-584. Society of Photo-Optical Instrumentation Engineers, 2001.
[14] J. Ruanaidh and T. Pun. Rotation, scale and translation invariant spread spectrum digital image watermarking. Signal processing, 66(3):303-317, 1998.
[15] J. Seo and C. Yoo. Image watermarking based on invariant regions of scale-space representation. IEEE transactions on Signal Processing, 54(4):1537-1549, 2006.
[16] S. Voloshynovskiy, A. Herrigel, N. Baumgaertner, and T. Pun. A stochastic approach to content adaptive digital image watermarking. In Information Hiding, pages 211-236. Springer, 1999.
[17] X. Wang, J. Wu, and P. Niu. A new digital image watermarking algorithm resilient to desynchronization attacks. IEEE Transactions on Information Forensics and Security, 2(4):655-663, 2007.
[18] A.B. Watson. Visually optimal DCT quantization matrices for individual images. In Data Compression Conference, pages 178-187. Citeseer, 1993.
[19] D. Zheng, S. Wang, and J. Zhao. RST invariant image watermarking algorithm with mathematical modeling and analysis of the watermarking processes. IEEE Transactions on Image Processing, 18(5):1055-1068, 2009.
[20] D. Zheng, J. Zhao, and A. El Saddik. RST-invariant digital image watermarking based on log-polar mapping and phase correlation. IEEE transactions on circuits and systems for video technology, 13(8):753-765, 2003.

指導教授

蘇柏齊(Po-chyi Su)

審核日期

2010-7-28

推文