FIDAC- Forged Images Detection And Classification
- Citation Author(s):
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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:
- DOI:
- 10.21227/4det-6512
- Data Format:
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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.
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