JPEG image forgery detection based on deep learning

Abstract:
With the development of the Internet, the JPEG format has become the mainstream format of digital images, and it has become very convenient to edit and tamper with images, making it more and more difficult to confirm the authenticity and integrity of images. Therefore, the research of image tampering forensics technology is of great significance. This paper studies the JPEG image tampering detection technology based on deep learning. For the tampered images after JPEG double compression, the convolutional neural network (CNN) model i n the field of deep learning is used, and it‘s powerful feature learning and model expression capabilities are used to extract The feature information of the JPEG image can detect the tampered image and locate the tampered area, and improve the accuracy of tampering detection and the localization accuracy of the tampered area.