International Journal of Advanced Innovative Technology in Engineering (IJAITE)

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Automated Image Forgery Detection With Python

Nidhi Gajimwar, Ashmi Dahiwale, Isha Walde, Shyamal Dhabarde, Prof. Monika Walde

Abstract :

Fake image detection has become increasingly important due to the widespread use of image editing software and the proliferation of fake images on social media and other online platforms. In this project, we propose a Python-based approach for detecting fake images using deep learning techniques. Our method involves preprocessing the images, extracting relevant features using convolutional neural networks (CNNs), and training a classifier to distinguish between real and fake images. We leverage state-of-the-art deep learning frameworks such as TensorFlow or PyTorch for model development and evaluation. Experimental results on benchmark datasets demonstrate the effectiveness of our approach in accurately identifying fake images. This project contributes to the ongoing efforts in combating misinformation and ensuring the authenticity of digital media content.

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