半脆弱浮水印在多媒體內容的驗證上，愈來愈受到密切的重視。最主要的原因是因為它具有判斷此數位內容是否遭受惡意竄改，甚至能指出惡意竄改位置的能力，非常適合現在許多的多媒體認證的應用。
為了能夠明確的分辨出偶然攻擊與惡意竄改，半脆弱浮水印對於各種較常見的影像處理具有一定的強韌性，像是普遍使用的JPEG壓縮及在網路傳輸中可能遭受的高斯雜訊等。因此基於內容的浮水印(content based watermark)便被大量的提出並應用，也就是從數位內容萃取出具強韌性的影像特徵當作浮水印嵌入，這樣一來便不需要原影像的輔助便能達到影像認證的效果。
在本篇論文中，我們的半脆弱浮水印系統主要是架構在Zernike moment上。因為Zernike moment具有很好的影像重建能力以及對影像旋轉等影像處理工具有極佳的抵抗能力，因此被用來當作此系統中最主要的影像特徵浮水印。另外，取此影像的邊緣(edge)來當作次要的影像特徵，目的是要利用此特徵的比對來輔助我們決定被惡意竄改的位置。
實驗結果證實此方法確實能順利指出被惡意竄改的區域，而且其偵側區塊只有8x8區塊，這使得在辨識被惡意竄改的區域更為準確。同時在強韌度方面，此系統能抵抗JPEG壓縮(Q>30)及高斯雜訊(variance<20)，對於像是旋轉等一般影像處理也不會發生錯誤。

This paper present a novel content-based image authentication framework which embeds the semi-fragile image feature into the host image based on wavelet transform. In this framework, two features of a target image from the low frequency domain to generate two watermarks: Zernike moments for classifying of the intentional content modification and sobel edge for indicating the modified location. In particular, we design a systematic method for automatic order selection of Zernike moments and in order to tell if the procession on the image is malicious or not, we also propose a weighted Euclidean distance by its reconstruction process. An important advantage of our approach is that it can tolerate compression and noise to a certain extent while rejecting common tampering to the image like rotation. Experimental results show that the framework can locate the malicious tamper locally, the unit of detection region is 8x8 block, while highly robust to content preserved processing, such as JPEG compression Q>=30 and Gaussian noise variance<=20.

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