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Image Forgery Detection with ELA and Deep Learning

Project objective

Combine the implementation of error-level analysis (ELA) and deep learning to detect whether an image has undergone fabrication or/and editing process or not, e.g. splicing.

Methods

  1. Error-level analysis
  2. Convolutional neural networks (CNN)

Activity Diagram

Activity-Diagram

Architecture

full-architecture

Result

  • Convergence: Epoch 30
  • Best accuracy: 98.13% (epoch 30)