BibTeX:

@article{IJIRSTV3I4143,
     title={An Efficient Approach for Detecting Exemplar Based Image Inpainting and Copy Move Forgery},
     author={Rinia Mary Varghese},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={4},
     pages={323--329},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I4143.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Today manipulation of digital images has become easy due to powerful computers, advanced photo-editing software packages and high resolution capturing devices. Verifying the integrity of images and detecting traces of tampering without requiring extra prior knowledge of the image content or any embedded watermarks is an important research field. Exemplar based inpainting and copy paste forgeries play visual tricks to deceive people and affect the authenticity of the images. The proposed method presents an efficient forgery detection algorithm for detecting the manipulation of images by exemplar inpainting and copy move forgery. The method shows an algorithm for object removal by exemplar-based image inpainting mechanism that restores the area of the removal object and the mechanism can be further employed to extract the back ground of images and it also detect the copy move forgery. Exemplar-based inpainting methods iteratively search the source region and fill the missing or damaged region, i.e., target region, with the most similar patch in the source region. The new method also shows a technique for detecting copy-move forgery over images tampered by copy-move. The proposed method integrates central pixel mapping (CPM), greatest zer connectivity component labeling (GZCL) and fragment splicing detection (FSD). CPM speeds up block search by efficiently matching those blocks with similar hash values and then finding the suspicious pairs. To improve the detection precision, GZCL is used to mark the tampered pixels in suspected block pairs. FSD is adopted t distinguish and locate tampered regions from its best-match regions. The algorithm can reduce the processing time and maintain a detection precision under different kinds of object-removed images. Detecting two forgeries by a single method makes it unique.

Image Inpainting, Forgery Detection, CPM