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The aim of this project is to detect copy move forgery in image forgery detection. Based on Deep learning techniques(CNN, NN)

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Lexymus/Copy-Move-forgery-Detection

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Copy-Move-forgery-Detection

The aim of this project is to detect copy move forgery in image forgery detection. Based on Deep learning techniques(CNN, NN) Tools or pakages used : python(3.7) Tensorflow(2.10) keras(2.10) matplotlib os opencv scipy segmentaion models PIL pandas

Datasets used:

  1. MICC_F2000 (http://lci.micc.unifi.it/labd/cmfd/MICC-F2000.zip)
  2. MICC_F220 (http://lci.micc.unifi.it/labd/cmfd/MICC-F220.zip)
  3. MICC_F600 (http://lci.micc.unifi.it/labd/cmfd/MICC_F600.zip)
  4. Coverage (https://1drv.ms/f/s!AggVhXcCj1FLhUUyUrqSpV_yI_GH)

for forgery detection first ELA is calculated then ElA images are trained.

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The aim of this project is to detect copy move forgery in image forgery detection. Based on Deep learning techniques(CNN, NN)

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