Detecting Fake Images Using Machine Learning
Mr. Akash K, Miss. Ahalya K, Mr. Dhinesh N, Miss. Diya Shereef M K · International Journal of Research Publication and Reviews · 2023
Fake image detection is an important problem in the field of computer vision and machine learning, as the use of manipulated images for deception or propaganda purposes is becoming increasingly common.In this paper, we propose a machine learning approach for detecting fake images, which is based on a combination of deep convolutional neural networks and traditional image processing techniques.Our method extracts a set of features from the input image, including statistical properties, color distributions, and texture information.These features are then fed into a classifier, which determines whether the image is genuine or manipulated.We evaluate our approach on a large dataset of real and fake images and demonstrate that it achieves state-of-the-art performance in terms of accuracy, precision, and recall.Our results suggest that machine learning methods can be effective for detecting fake images and have the potential to be used in a wide range of applications, including social media content moderation, news verification, and forensic analysis.