Multi-Classifier Ensemble for Content- Preserving Image Forgery Detection: A SVM and CNN-Based Approach

A novel approach for detecting content-preserving image forgeries using SVM and CNN-based ensemble classifiers

Authors

  • Gupta Avdheshkumar
  • Dr. Ashish Chourasia

Keywords:

digital image forgery detection, content-preserving image forgeries, support vector machines, convolutional neural networks, ensemble classifiers, machine learning algorithm

Abstract

Digital image forgery detection has become increasingly important due to the proliferation ofimage editing software and the rise in image-based social media platforms. Content-preserving forgeriespose a significant challenge to existing forgery detection techniques since they aim to maintain thevisual appearance of an image while introducing subtle alterations. This research paper proposes anovel method for detecting content-preserving image forgeries using Support Vector Machines (SVM),Convolutional Neural Networks (CNN), and ensemble classifiers of the machine learning algorithm.

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Published

2022-04-01

How to Cite

[1]
“Multi-Classifier Ensemble for Content- Preserving Image Forgery Detection: A SVM and CNN-Based Approach: A novel approach for detecting content-preserving image forgeries using SVM and CNN-based ensemble classifiers”, JASRAE, vol. 19, no. 3, pp. 457–459, Apr. 2022, Accessed: Jul. 03, 2024. [Online]. Available: https://ignited.in/jasrae/article/view/13902

How to Cite

[1]
“Multi-Classifier Ensemble for Content- Preserving Image Forgery Detection: A SVM and CNN-Based Approach: A novel approach for detecting content-preserving image forgeries using SVM and CNN-based ensemble classifiers”, JASRAE, vol. 19, no. 3, pp. 457–459, Apr. 2022, Accessed: Jul. 03, 2024. [Online]. Available: https://ignited.in/jasrae/article/view/13902