FIDAC- Forged Images Detection And Classification

Citation Author(s):
Shraddha
Pawar
Student at Shah & Anchor Kutchhi Engineering College
Gaurangi
Pradhan
Student at Shah & Anchor Kutchhi Engineering College
Bhavin
Goswami
Student at Shah & Anchor Kutchhi Engineering College
Sonali
Bhutad
Professor at Shah & Anchor Kutchhi Engineering College
Submitted by:
Shraddha Pawar
Last updated:
Fri, 04/08/2022 - 06:27
DOI:
10.21227/4det-6512
Data Format:
Image files
License:
Creative Commons Attribution
476 Views
Categories:
Artificial Intelligence
Image Processing
Keywords:
Forgery, image tampering, image classification, fake images, authentic images
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Abstract 

This dataset consists of 2 types of images i.e Authentic and Tampered. There are a total of 1,389 Authentic images and 597 Tampered images. Authentic images are camera clicked images in raw form & tampered images are the one being edited by Adobe Photoshop and few mobile applications. Different types of forgery techniques like copy-move, splicing, color enhancement, resizing etc have been applied on the tampered images. 

The main motive of this dataset is to optimize the AI/ML based fake image identification model. Thus, this dataset is used for the R&D of fake image classification. 

Instructions: 

  • The dataset consists of a total of 1986 images in  *.png, *.jpg, *.jpeg files formats.

  • The dataset requires a space of 5 GB.

  • The dataset consists of two folders namely Authentic_Images & Tampered_Images.

Dataset Files

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Documentation

AttachmentSize
File FIDAC.txt971 bytes

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