Texture Operator Based Image Splicing Detection Hybrid Technique

Image splicing is performed for malicious purposes and it is trouble-free due to the availability of simple to use image editing applications. In this paper, we use standard deviation filter to highlight the image details and then apply rotation invariant co-occurrence among adjacent local binary pattern (RIC-LBP) operator to extract the internal statistical information. The standard deviation filter is used in Synthetic Aperture Radar images to detect an object and oil in sea. This filter highlights the abrupt changes in Synthetic Aperture Radar images. In image splicing when two or more images are used to create forged images the abrupt changes occur that are highlighted using standard deviation filter. The RIC-LBP operator provides internal statistics of the image due to its high descriptive ability. We use Columbia database and DSO-1 database for performance evaluation and use Spectral Regression Discriminant Analysis as a classifier. Our method outperforms some of the state of the art methods.