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Abstract

The main issue in image forensics is to discover whether an image is authentic or forged and, if forged, to locate which regions have been manipulated. The simple accessibility of image manipulation software have proliferated the possibility of image forgery. Detection of Splicing forgery is targeted in this paper. Noise component of a color image have been utilized to extract features from suspected image. As the consistency of noise between RGB color channel of forged and authentic image are different, so it leaves the clues of forgery. First digit features are extracted using Benfords’ law and provided to the SVM classifier Columbia uncompressed image splicing detection evaluation dataset and CASIA v1.0 dataset are used to test the proposed technique. Our technique outperforms various previous techniques of image splicing detection.

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Keywords

Forgery Detection, Image Forensics, Low Contrast, Splicing Forgery.