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DOI: 10.14569/IJACSA.2020.0111164
PDF

Object based Image Splicing Localization using Block Artificial Grids

Author 1: P N R L Chandra Sekhar
Author 2: T N Shankar

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 11, 2020.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: People share pictures freely with their loved ones and others using smartphones or social networking sites. The news industry and the court of law use the pictures as evidence for their investigation. Simultaneously, user-friendly photo editing tools alter the content of pictures and make their validity ques-tionable. Over two decades, research work is going on in image forensics to determine the picture’s trustworthiness. This paper proposes an efficient statistical method based on Block Artificial Grids in double compressed images to identify regions attacked by image manipulation. In contrast to existing approaches, the proposed approach extracts the artefacts on individual objects instead of the entire image. A localized algorithm is proposed based on the cosine dissimilarity between objects and exploit the tampered object with maximum dissimilarity among objects. The experimental results reveals that the proposed method is superior over other current methods.

Keywords: Image forensics; splicing localization; block artifi-cial grids; object segmentation; double compression

P N R L Chandra Sekhar and T N Shankar, “Object based Image Splicing Localization using Block Artificial Grids” International Journal of Advanced Computer Science and Applications(IJACSA), 11(11), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111164

@article{Sekhar2020,
title = {Object based Image Splicing Localization using Block Artificial Grids},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111164},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111164},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {11},
author = {P N R L Chandra Sekhar and T N Shankar}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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