Image Forgery Authentication and Classification using Hybridization of HMM and SVM Classifier

Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Security
Format: PDF
Image forgery is a major issue in today's digital publishing and printing. Now-a-days, system can be used for forensic purpose to validate the authenticity of an image. In this paper, the authors present an approach for image forgery authentication. They observe that a non-morphed and non-forged image shows homogeneity in non-spectral domain. This homogeneity is lost when any forgery or morphing is applied on the images. They therefore apply a set of transform over the images. They combine DCT statistics, LBP features with curvelet statistics and Gabor transform of the images to represent an image in the transformed domain.

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