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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM28017

Automated Detection of Image Forgery Based on Machine Learning: A Review

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM28017

Volume:

8 |

1 |

Jan 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MMS

Muskan Mohd. Shabir

DMV

Dr. Manish Vyas

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Abstract

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.

Cite This Article

Muskan Mohd. Shabir, Dr. Manish Vyas, "Automated Detection of Image Forgery Based on Machine Learning: A Review," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 1, Jan 2024.

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12/31/45300

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Double-Blind Peer Review

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