Image integrity and tampering detection: A hybrid approach to copy-paste forgery detection using ORB-SSD and CNN

Digital image manipulation, especially copy-paste forgery, presents significant challenges to maintaining the authenticity and credibility of visual content in the digital age. As image editing techniques become increasingly sophisticated, there is a pressing need for effective and reliable methods to detect and localize manipulated regions within images. This study introduces an innovative approach that combines ORB (Oriented FAST and Rotated BRIEF) and SSD (Single Shot Detector) algorithms for key point detection and feature matching, complemented by a CNN-based image authentication process. The low-dimensional binary descriptors generated by the ORB method enhance computational efficiency, while the integration of SSD ensures precise localization of fraudulent areas. Experimental evaluations, using metrics such as precision, recall, and F1-score, demonstrate the proposed method's superior performance compared to existing state-of-the-art techniques, achieving a favorable balance between accuracy and processing speed. This approach effectively detects copy-paste forgeries, even in complex scenarios, providing a reliable tool for identifying altered digital images. The methodology has potential applications in digital forensics, copyright protection, and secure multimedia content verification.