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Image Tampering Detection with ELA and Deep Learning

  • Unique Paper ID: 165278
  • Volume: 11
  • Issue: 1
  • PageNo: 788-794
  • Abstract:
  • Photographs are the foremost powerful and trustworthy media of expression. At present, digital images not only give forged information but also work as agents of secret communication. Users and editing professionals manipulate digital images with various objectives. In fact, images are often considered as evidence of a fact or reality, therefore, fake news or any form of publication that uses images that have been manipulated in such a way as to have the capability and greater potential for misleading. To detect falsification of the image, image data is required in large quantities multiple, and a model that can process every pixel in picture. In addition, efficiency and flexibility in data training is also needed to support its use in everyday life. Deep learning concepts like Convolutional Neural Network (CNN) with Error Level Analysis is the perfect solution for this problem.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 1
  • PageNo: 788-794

Image Tampering Detection with ELA and Deep Learning

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