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Research Article |

Image Forgery Detection Using Integrated Convolution-LSTM (2D) and Convolution (2D)

Author(s): Yogita Shelar1*, Dr. Prashant Sharma2 and Dr.Chandan Singh. D. Rawat3

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 2 ,   Special Issue on Mobile Computing assisted by Artificial Intelligent for 5G/6G Radio Communication

Publisher : FOREX Publication

Published : 30 June 2023

e-ISSN : 2347-470X

Page(s) : 631-638

DOI: https://doi.org/10.37391/ijeer.110253

Abstract

Digital forensics and computer vision must explore image forgery detection and their related technologies. Image fraud detection is expanding as sophisticated image editing software becomes more accessible. This makes changing photos easier than with the older methods. Convolution LSTM (1D) and Convolution LSTM (2D) + Convolution (2D) are popular deep learning models. We tested them using the public CASIA.2.0 image forgery database. ConvLSTM (2D) and its combination outperformed ConvLSTM (1D) in accuracy, precision, recall, and F1-score. We also provided a related work on image forgery detection models and methods. We also reviewed publicly available datasets used in picture forgery detection research, highlighting their merits and drawbacks. Our investigation revealed the state of picture fraud detection and the deep learning models that worked well. Our work greatly impacts fraudulent photo detection. First, it highlights how important deep learning models are for picture forgery detection. Second, ConvLSTM (2D) + Conv (2D) detect image forgeries better than ConvLSTM (1D). Finally, our dataset analysis and proposed integrated approach help research construct more effective and accurate picture forgery detection systems.

Keywords: ConvLSTM, Image Forgery Detection, deep learning, CASIA v2.0, convolutional neural networks.




Yogita Shelar*, Research scholar, Department of Computer Science, Pacific Institute of Technology, Udaipur, India; Email: yogitamshelar@gmail.com

Dr. Prashant Sharma, Assosiate Professor, Department of Computer science, Pacific Institute of Technology, Udaipur, India; Email: prashant.sharma@pacificit.ac.in

Dr.Chandan Singh. D. Rawat, Head Of Department of Electronic and Telecommunication Vivekanand Education Society's Institute of Technology, Chembur, India; Email: chandansingh.rawat@ves.ac.in

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Yogita Shelar, Dr. Prashant Sharma and Dr. Chandan Singh. D. Rawat (2023), Image Forgery Detection Using Integrated Convolution-LSTM (2D) and Convolution (2D). IJEER 11(2), 631-638. DOI: 10.37391/ijeer.110253.