Open AccessMedical Image Forgery Detection using Cnn
Author(s) -
Manoj Kumar,
J. Preethi,
J. Sandhya,
Inti Satyapriya Harshini
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f3558.049620
Subject(s) - computer science , convolutional neural network , variety (cybernetics) , image (mathematics) , artificial intelligence , convolution (computer science) , computer security , computer vision , artificial neural network
With the improvement of the computer technology, image processing techniques have become important in a wide variety of medical applications. Numerous new features have been added to satisfy people. People consult doctors online, without even visiting them. As health is a critical issue, we should take care with full attention and security. This paper proposes a medical image forgery detection system for the identifying whether the image is altered or not. The forgery done on the medical images can lead to various issues that can shake the medical industry this also promotes wrong diagnosis, organ trafficking etc. Hence a group of different forgery detection algorithms is described and by using the Convolution neural networks we can detect and the forged images. This paper also gives a brief outline about the advantages and disadvantages of the existing systems in forgery detection.