隨著數位多媒體資料持續增加與廣泛應用，多媒體安全在保護其內容免於非法使用變得愈來愈重要。數位浮水印是應用於多媒體安全上處理這些議題的核心技術，例如版權保護、內容認證和竄改偵測。近來很多針對這些目標的浮水印研究被提出，但是在實際應用仍然存在著一些困難，包含強健性與安全性等。因此，本論文針對多媒體安全提出一個新穎的基於特徵之數位浮水印架構和其相對應的基本設計原則，藉著同時考量多媒體內容屬性和浮水印需要性以偵測出適當的特徵，接著根據特徵值挑選出最好的區域集合，與浮水印資訊結合達到最佳的效能。基於前述所提的架構，我們將其具體實現於二維影像和三維網格浮水印方法以驗證效能。在二維影像浮水印方法中，我們利用尺度適應性自相關矩陣和高斯拉普拉斯運算從目標影像中獲得特徵區域，並且建構一個選擇程序評估特徵區域的屬性，用以決定一個最佳的區域集合來嵌入浮水印的資訊，它可以針對各種攻擊達到最大的強健性，並且可以盡量保有影像本身的品質，我們也在偵測與選取特徵區域的程序加入隨機性來強化安全性，用以防止浮水印資訊被未授權的惡意使用者任意的存取。在三維網格浮水印方法中，首先從目標網格模型中偵測出可抵抗姿勢改變的特徵，包含三維的表面距離和形狀直徑特徵值，接著建構特徵的直方圖以結合浮水印資訊，達到在保有一定的強健性下具有最小的失真度。最後，我們以充分的實驗與分析結果具體呈現所提出的架構具可行性及有效性。

With the proliferation of digital multimedia data, multimedia security has become increasingly important to protect the content from illegal uses. Digital watermarking is a core enabling technology for multimedia security to deal with the issues in multimedia applications, such as copyright protection, content authentication and tampering detection. Recently, much research in this technology has been proposed for the purpose, but there are still some challenging difficulties for achieving robustness and security. In this dissertation, a new feature-based watermarking framework and its fundamental design principles are presented to mitigate the difficulties. We begin with detecting good features by jointly considering multimedia properties and watermarking requirements. An optimal region set is selected according to the detected features and linked with watermark information to achieve a desired goal. The framework is implemented in two-dimensional (2D) image and three-dimensional (3D) mesh watermarking to verify its performance. In the 2D image watermarking, local features are obtained from a target image based on the scale-adapted auto-correction matrix and the Laplacian-of-Gaussian operation. A selection process is then constructed to choose a feature region set, which has the greatest robustness against various attacks and can preserve image quality as much as possible after being watermarked. Moreover, we incorporate randomization in determining features to mitigate the leakage of secret information for enhancing watermarking security. In the 3D mesh watermarking, pose-oblivious features that include the geodesic distance and the local shape diameter are detected from a target mesh model. We build histograms of these features for watermarking to minimize mesh distortions while keeping robustness. Extensive experiments and analyses are conducted to clearly demonstrate the effectiveness of our proposed framework.

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