利用色彩濾片陣列及旋轉不變特性之影像鑑識系統

Image Forensics System Utilizing Color Filter Array and Rotation Invariant Property

廖正豪(Cheng-Hao Liao)

指導教授 ： 郭天穎

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2010年)

https://doi.org/10.6841/NTUT.2010.00071

摘要

近幾年來，由於數位成像裝置與先進的影像編輯軟體廣泛且盛行地使用，使得數位影像容易被建立也容易遭受篡改。因此，數位影像鑑識技術演變為現今重要的議題。在本論文中，我們發展一多重偵測技術的影像鑑識系統，整合了兩種文獻方法及所提出的兩個新方法。
我們所提出的第一個方法是利用色彩濾片陣列(Color Filter Array, CFA)週期性質並改進文獻Expectation Maximization (EM)演算法以獲取最大事後機率(Maximum A Posterior Probability, MAP)，可自動判別相片影像與電腦合成影像，且可自動找出遭受篡改之區域。第二個提出的方法著重於複製區域(Duplicated Region)的篡改偵測，偵測之方法為對測試影像分割為圓形區塊，計算每個圓形區塊之同心圓平均值及澤尼克動量(Zernike Moments)做為特徵向量，並將所有特徵向量進行字典式排序，隨後搜尋相似匹配對，最終由定義之相似度閥值來判斷相似的圓形區塊。與文獻方法相比，我們的方法能夠偵測複製區域篡改之任意角度旋轉與水平、垂直翻轉。實驗的結果與分析證實所提出之方法在篡改偵測中具有強健性。

關鍵字

影像鑑識 ； 來源辨識 ； 篡改偵測 ； 色彩濾片陣列 ； 複製區域偵測 ； 澤尼克動量

並列摘要

In recent years, due to the widespread use of digital imaging devices and sophisticated image editing software, it is getting easier to create and alter digital images. As a result, digital image forensics techniques become an important issue nowadays. In this thesis, we develop an image forensics system based on multiple detection techniques, including two existing literature approaches and the proposed two new methods.
Our first proposed method is based on the Color Filter Array (CFA) periodic characteristics. We improve the literature Expectation Maximization (EM) algorithm to get the Maximum A Posterior Probability (MAP) for distinguishing photographic images and photorealistic computer generated images. It can also helps localize tampered image regions automatically. The second proposed method concentrates on forgery detection on duplicated region. The suspicious image is split into circle blocks, and then the concentric circle mean and Zernike moments are calculated as the feature vectors for every circle block. The feature vectors are sorted by lexicographical order, and then searched for similar pairs. Thus, the similar circle blocks can be matched by a pre-defined similarity threshold. Compared with the literature methods, our methods can improve the detection of the duplicated region forgery with any angle rotation and vertical and horizontal flipping. The experimental results and analyses demonstrate that the proposed methods are robust in forgery detection.

並列關鍵字

Image Forensics ； Source Identification ； Tamper Detection ； Color Filter Array ； Duplicated Region Detection ； Zernike Moments

參考文獻

[1] A. Haouzia and R. Noumeir, “Methods for Image Authentication: A Survey,” Springer Netherlands, Multimedia Tools and Applications, Vol. 39. No. 1, pp. 1-46, Aug. 2008.

[2] H. Farid, “Digital Image Forensics,” Scientific American Magazine, pp. 66-71, June 2008.

[3] H. T. Sencar and N. Memon, “Overview of State-of-the-Art in Digital Image Forensics,” Statistical Science and Interdisciplinary Research. World Scientific Press, Singapore, 2008.

[4] B. Mahdian and S. Saic, “Blind Methods for Detecting Image Fakery,” IEEE International Carnahan Conference on Security Technology, pp. 280-286, Oct. 2008.

[5] T. V. Lanh, K. S. Chong, S. Emmanuel and M. S. Kankanhalli, “A Survey on Digital Camera Image Forensic Methods,” IEEE International Conference on Multimedia and Expo, pp. 16-19, July 2007.