Copy-Move Forgery Detection in Medical Images Using Handcrafted Features

Abstract

Abstract: In the realm of medical imaging, the authenticity and integrity of images are paramount for accurate diagnosis and treatment planning. Copy-move forgery, a prevalent form of image tampering, poses a significant threat to the reliability of medical images. This research project focuses on the development and implementation of a robust copy-move forgery detection system tailored specifically for medical images. The proposed methodology leverages handcrafted features, extracting distinctive characteristics from the images to detect instances of forgery. Through a meticulous process of feature engineering and selection, the algorithm aims to enhance sensitivity and specificity in identifying manipulated regions within medical images. The study explores the application of advanced image processing techniques and pattern recognition algorithms to achieve a high level of accuracy in forgery detection.