Detecting doctored images using camera response normality and consistency

The advance in image/video editing techniques has facilitated people in synthesizing realistic images/videos that may hard to be distinguished from real ones by visual examination. This poses a problem: how to differentiate real images/videos from doctored ones? This is a serious problem because som...

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Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 1087 - 1092 vol. 1
Main Authors Zhouchen Lin, Rongrong Wang, Xiaoou Tang, Heung-Yeung Shum
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Asia
Cameras
Colored noise
Humans
Interpolation
Protection
Signal synthesis
Support vector machines
Testing
Watermarking
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Summary:The advance in image/video editing techniques has facilitated people in synthesizing realistic images/videos that may hard to be distinguished from real ones by visual examination. This poses a problem: how to differentiate real images/videos from doctored ones? This is a serious problem because some legal issues may occur if there is no reliable way for doctored image/video detection when human inspection fails. Digital watermarking cannot solve this problem completely. We propose an approach that computes the response functions of the camera by selecting appropriate patches in different ways. An image may be doctored if the response functions are abnormal or inconsistent to each other. The normality of the response functions is classified by a trained support vector machine (SVM). Experiments show that our method is effective for high-contrast images with many textureless edges.
ISBN:0769523722
9780769523729
ISSN:1063-6919
DOI:10.1109/CVPR.2005.125