數位影像的快速增加以及影像編輯軟體的容易取得，使得數位影像受到人為合成以及其他竄改的情形也日益嚴重。因此，數位鑑識(Digital Forensics)的重要性逐漸提高，也成為一個重要且發展迅速的研究主題，而在數位鑑識的研究領域中，主要有：偵測數位影像偽造(digital image forgery detection)，以及相機來源辨識(camera source identification)。在本篇論文中，我們的重點在於偵測數位影像偽造，JPEG影像壓縮技術是目前重要的影像儲存格式之一，離散餘弦變換(DCT transformation)以及量化(quantization)是JPEG壓縮編碼的兩個主要流程，量化表(quantization table)是用來量化離散餘弦變換後的數值(DCT coefficients)，並且已被認為是可利用於偵測數位影像偽造的有效特徵。因此，我們透過找尋不同JPEG壓縮區塊(JPEG blocks)中是否存在不一致的JPEG壓縮特性，來偵測數位影像中是否經過偽造。首先我們提出估計量化表的方法，利用估計出來的量化表計算每區塊對應的量化誤差(quantization error)，最後透過找尋異常大的量化誤差用以偵測影像偽造的區域。實驗數據顯示我們提出的估計量化表的方法準確性高過現有的方法，並且針對數種不同的數位影像偽造皆能有效偵測出偽造區域。

Digital image forgery detection becomes an important research topic in digital image forensics. JPEG is a popular file format for digital image now. DCT transformation and quantization are two main parts of JPEG encoding process. Quantization table is used for quantizing the DCT coefficients and has been proved as an effective feature for image forgery detection. In this thesis, we propose a method to detect image forgery by detecting inconsistency of JPEG encoded blocks. First, we estimate the quantization table of a JPEG compressed image. Then, we measure the block quantization error using estimated quantization table. Finally, we detect the forged region with large block quantization error by thresholding. In the experimental results, we show that our proposed quantization table estimation method outperforms the existing methods and our proposed image forgery detection algorithm performs well in different forgery type, including copy-move, splicing, image inpainting, image resizing, cropping, and recompression.

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[8] Software available at http://www.intuimage.com/
[9] Software available at http://www.hanovsolutions.com/?prod=PhotoWipe