臺灣博碩士論文加值系統

H.264是一個新興的視訊壓縮標準，現今不論是在有線或無線網路的視訊應用上，都相當受到歡迎。然而數位內容容易被消費者修改或是拷貝，因此著作權保護、拷貝控制和完整驗證，在近幾年已變成一個重要的議題。浮水印即是一種要求數位資料所有權的保護方法。
本論文中我們利用區塊極性與序號調變來達到浮水印的嵌入，其中區塊極性是由4x4 DCT轉換且量化後的DC係數來決定，而區塊序號則是由4x4 DCT轉換且量化後，其所有AC係數量級的總和來決定。區塊序號的最低位元被當成調變參數，藉由修改量化之AC係數來改變調變參數，進而達到嵌入浮水印的目的。為了抵抗時軸同步攻擊，像是畫面刪除，畫面插入或是畫面順序調換，我們亦提出基於特徵統計的時軸同步機制，特徵統計量是經由統計視訊內容中的局部變異量或是特徵空間分佈的投影量而得到，同時將其當作額外資訊傳送到浮水印萃取端。在浮水印萃取端，藉由比對額外資訊與從接收視訊中取出的特徵統計量，來達到時軸同步。
模擬結果顯示提出的浮水印系統有良好的效能，而且萃取浮水印不需要原始視訊，同時浮水印演算法有較低的複雜度，可適合即時性的應用；而基於特徵統計的時軸同步機制，可促使浮水印系統更有效的抵抗時軸同步攻擊。

H.264 is a new advanced standard. The applications of video on Internet or wireless networks become very popular nowadays. However, these digital contents can be easily modified and copied by end users. Hence copyright protection, copy control and integrity verification has become important issues in recent years. Digital watermarking is a means of claiming ownership of a data source.
In the proposed system, block polarity and block index modulation are used to achieve watermark embedding. The block polarity is determined based on the nonzero quantized DC coefficient in each 4x4 integer DCT block. The block index is the pseudo-quantized block activity that is represented by the sum of magnitude of quantized AC coefficients. The watermark embedding is actually performed by the index modulation that will modify quantized AC coefficient values by a small amount to force the activity to be quantized into a specific region.
For resisting temporal attacks, such as frame dropping, frame insertion, and frame transposition, we also propose a temporal synchronization method for video watermarking by matching feature statistics. The feature statistics are calculated by local variances or eigenvalues in video content and sent as side information. Temporal attacks can be detected by comparing side information and feature statistics that be calculated from the received video.
Simulation results show that the proposed method performs well and extract embedded watermark without the original video signal. Additionally, the algorithm is not very complex and appropriate for real-time applications. Based on the extracted feature statistics, the video watermarking system is more robustness against temporal attacks.

目錄
摘 要 I
Abstract II
目錄 III
圖目 VI
表目 IX
第一章 序論 1
1.1 研究動機與目的 1
1.2 數位浮水印概論 4
1.2.1 數位浮水印之應用 8
1.2.2 數位浮水印同步簡介 10
1.3 論文架構 12
第二章 視訊浮水印的發展 13
2.1 視訊浮水印之功能需求 13
2.2 視訊浮水印技術回顧 17
2.3 同步攻擊及同步技術發展 19
2.3.1 同步攻擊 20
2.3.2 同步技術發展 22
2.4 H.264視訊壓縮標準簡介 25
2.4.1 整體壓縮效能改進情形 26
2.4.2 H.264架構介紹 27
2.4.3 網路提取層 28
2.4.4 視訊編碼層 29
第三章 H.264序號調變視訊浮水印系統 41
3.1 系統嵌入架構 41
3.2 數位浮水印嵌入演算法 44
3.2.1 決定區塊極性 (Block Polarity Decision) 45
3.2.2 區塊序號調變(Block Activity Index Modulation) 46
3.3 數位浮水印萃取演算法 50
第四章 特徵統計之時軸同步機制 51
4.1 系統架構 51
4.2 同步訊號產生 53
4.2.1 局部變異量統計 53
4.2.2 固有值統計 55
4.3 同步訊號偵測 59
第五章 實驗結果與討論 61
5.1 實驗參數環境 61
5.2 H.264視訊浮水印分析 63
5.2.1 浮水印透明度 63
5.2.2 浮水印強韌度 67
5.3 時軸同步測試 76
第六章 81
參考文獻 82

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