利用多尺度區域雜訊不一致性之影像拼接偵測

卓宥亦

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利用多尺度區域雜訊不一致性之影像拼接偵測

Image Splicing Detection Using Inconsistent Multi-scale Local Noise Variances

卓宥亦 , Masters　　Advisor：郭天穎　　

繁體中文

影像鑑識；篡改偵測；吉伯斯隨機場；主成分分析；多尺度； Image forensics ； Tampering detection ； Gibbs random field ； Principal component analysis ； Multi-scale

Abstract │ Reference (36) │ Altmetrics

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Due to the rapid development of image editing software, it becomes easy to tamper a digital image and create a fake image. One of the common and simple ways of the digital image tampering is image splicing, which is to copy a region of an image to another image, and add the contents not belonging to the original image. Therefore, the authenticity of digital image has become an important issue.
    Since different sources of images are productions of different sensors and post-processing, they will contain different noise levels. Based on this fact, we propose a multi-scale PCA noise level estimation algorithm to detect image splicing, and improve the detection rate of the existing works. In addition, our method can locate the tampering region by clustering the estimated noise with the integration of EGB segmentation. In the experiments, we use the Columbia uncompressed image splicing detection evaluation dataset to test our method. The experimental results show that our method can detect the image splicing robustly and accurately.

Reference ( 36 ) 〈TOP〉

[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.
連結：
[2] H. Farid, “Digital Image Forensics,” Scientific American Magazine, pp. 66-71, Jun. 2008.
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[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.
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[4] B. Mahdian and S. Saic, “Blind Methods for Detecting Image Fakery,” IEEE International Carnahan Conference on Security Technology, pp. 280-286, Oct. 2008.
連結：
[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, Jul. 2007.
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