Detecting Forged Images with Machine Learning
Document Type
Oral Presentation
Campus where you would like to present
Ellensburg
Event Website
https://digitalcommons.cwu.edu/source
Start Date
18-5-2020
Abstract
The issue of forged images is now a global problem which mainly spreads via social network. Image forgery has weakened people's confidence in digital photos. Many researchers have devoted extensive research contributions in recent years to the development of new techniques to combat various image forgery attacks. Automatically detecting fake images may protect people from being victims of forged photos that can deceive and cause harm to others. Our contribution is a hybrid method which combines Error Level Analysis and deep learning for detecting manipulated images. According to our preliminary experimental results, the combination of image pre-processing and machine learning techniques is an efficient approach detecting image forgery attacks.
Recommended Citation
Alzamil, Lubna, "Detecting Forged Images with Machine Learning" (2020). Symposium Of University Research and Creative Expression (SOURCE). 42.
https://digitalcommons.cwu.edu/source/2020/COTS/42
Department/Program
Computer Sciences
Additional Mentoring Department
https://cwu.studentopportunitycenter.com/2020/04/detecting-forged-images-with-machine-learning/
Detecting Forged Images with Machine Learning
Ellensburg
The issue of forged images is now a global problem which mainly spreads via social network. Image forgery has weakened people's confidence in digital photos. Many researchers have devoted extensive research contributions in recent years to the development of new techniques to combat various image forgery attacks. Automatically detecting fake images may protect people from being victims of forged photos that can deceive and cause harm to others. Our contribution is a hybrid method which combines Error Level Analysis and deep learning for detecting manipulated images. According to our preliminary experimental results, the combination of image pre-processing and machine learning techniques is an efficient approach detecting image forgery attacks.
https://digitalcommons.cwu.edu/source/2020/COTS/42
Faculty Mentor(s)
Razvan Andonie