A Survey on Machine Learning Based Approaches for Detection of Image Forgery

A Survey on Machine Learning Based Approaches for Detection of Image Forgery

Madhu Malviya1, Prof. Sanmati Jain2

Image Forgery has been a very prevalent incidence in the recent times. With the rise in usage of the digital platforms and proliferation of digitization and social media in social and corporate sphere, images and multimedia have become indispensable. The image data generation has been enormous and its applications have also been quite vast. Consequently, it has led to misuse as well. Image Forgery has become a very grave concern in the world. Forged images can lead to major and innumerable problems and incur critical damages. So, Image Forgery detection is a very important mechanism to combat such incidents. The Image Forgery detection system has to very robust and yield accuracy and precision as it has to deal with large and complex data sets of images [1]. Therefore, the use of Artificial Neural Networks is a very sophisticated method for the same. This paper discusses the ANN approach for the Image Forgery Detection.

Keywords—Image Forgery, Artificial Neural Network (ANN), Accuracy, Precision.