A New Method for Forensic Detection of Image Manipulation

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    As the use of digital images has expanded, so has the methods and the motivating force to make advanced picture frauds. As needs be, there is an incredible requirement for advanced image legal sciences methods equipped for identifying image changes and manufactured images. We demonstrate that pixel value mappings desert factual follows which we might allude to as a mappings inherent unique finger impression in an image pixel value histogram. We at that point propose scientific techniques for recognizing general structures all around and privately connected complexity upgrade and in addition a strategy for distinguishing the utilization of histogram leveling via hunting down the recognizing highlights of every task intrinsic fingerprint. Also we propose a technique to identify the worldwide expansion of noise to a formerly JPEG - compacted image by watching that the key fingerprint of a particular planning will be adjusted on the off chance that it is connected to a image’s pixel value after the noise addition.

     

     

  • Keywords


    Pixel Value Histogram; Intrinsic Fingerprint; Pixel Value Mapping

  • References


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      [2] M. C. Stamm and K. J. R. Liu, "Forensic detection of image tampering using intrinsic statistical fingerprints in histograms," in Proc. APSIPA Annual Summit and Conf., Sapporo, Japan, Oct. 2009.

      [3] I. Avcibas, S. Bayram, N. Memon, M. Ramkumar, and B. Sankur, "A classifier design for detecting image manipulations," in Proc. ICIP, Oct. 2004, vol. 4, pp. 2645-2648.

      [4] M. K. Johnson and H. Farid, “Exposing digital forgeries by detecting inconsistencies in lighting,” in Proc. ACM Multimedia and Security Workshop, New York, NY, 2005, pp. 1–10.

      [5] D.Femi, S.Thylashri, S.Ravikumar ,” A Flexible Data Hiding Scheme Using Differential Dual Mapping,” in International Journal of Engineering & Technology Vol 7, No 1.7 2018 pp 68-70.

      [6] J. Lukás, J. Fridrich, and M. Goljan, “Detecting digital image forgeries ˇ using sensor pattern noise,” in Proc. SPIE, Electronic Imaging, Security, Steganography, Watermarking of Multimedia Contents, San Jose, CA, Feb. 2006, vol. 6072, pp. 362–372.

      [7] J. Fridrich, D. Soukal, and J. Lukás, “Detection of copy-move forgery in digital images,” in Proc. Digital Forensic Research Workshop, Cleveland, OH, 2003.


 

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Article ID: 15048
 
DOI: 10.14419/ijet.v7i2.19.15048




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