Enhancing Image Forgery Detection: A Novel Method for Content-Preserving Forgeries using Machine Learning Algorithms

Improving Accuracy and Reliability of Image Forgery Detection using Machine Learning

Authors

  • Gupta Avdheshkumar
  • Dr. Ashish Chourasia

Keywords:

image forgery detection, content-preserving forgeries, machine learning algorithms, support vector machines, convolutional neural networks, ensemble classifiers, accuracy, reliability

Abstract

Digital image forgery has become a significant concern due to the ease of manipulating anddistributing digital media. Content-preserving forgeries are particularly challenging to detect, as theymaintain the visual integrity of the original image while altering its content. In this research paper, wepropose a novel image forgery detection method that combines Support Vector Machines (SVM),Convolutional Neural Networks (CNN), and ensemble classifiers to enhance the accuracy and reliabilityof forgery detection.

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Published

2021-12-01

How to Cite

[1]
“Enhancing Image Forgery Detection: A Novel Method for Content-Preserving Forgeries using Machine Learning Algorithms: Improving Accuracy and Reliability of Image Forgery Detection using Machine Learning”, JASRAE, vol. 18, no. 7, pp. 462–463, Dec. 2021, Accessed: Jul. 03, 2024. [Online]. Available: https://ignited.in/jasrae/article/view/13671

How to Cite

[1]
“Enhancing Image Forgery Detection: A Novel Method for Content-Preserving Forgeries using Machine Learning Algorithms: Improving Accuracy and Reliability of Image Forgery Detection using Machine Learning”, JASRAE, vol. 18, no. 7, pp. 462–463, Dec. 2021, Accessed: Jul. 03, 2024. [Online]. Available: https://ignited.in/jasrae/article/view/13671