,Zahraa Aqeel Salih, Rasha Thabit, Khamis A. Zidan,
Abstract
Recently, the research community spent a lot of effort to present face image manipulation detection techniques, however, all the available schemes have their own limitations and there is no global detection scheme. To avoid the problems that can face the deep-learning based techniques, we suggest another direction of research to implement a new Face Image Manipulation Detection (FIMD) scheme which is based on face detection and image watermarking techniques. The proposed FIMD scheme at the sender side has two stages where the first stage is applied to detect and select the face area and the second stage is applied to generate and embed the manipulation detection and localization data. The proposed FIMD scheme at the receiver side has also two stages where the first stage is applied to detect and select the face area and the second stage is applied to extract the embedded data and check the authenticity of the received face image. The experiments that have been conducted to check the performance of the proposed FIMD scheme proved its efficiency in detecting different types of face manipulations such as face swap, expression swap, attribute attacks, and retouching attacks. The detection accuracy is 100 % and no false detection results have been recorded, in addition, the scheme obtained promising results in terms of visual quality of the watermarked face images and high embedding capacity. The general comparison with the state-of-the-art detection schemes proved the superiority of the proposed FIMD scheme.
أ د خميس عواد زيدان | Khamis A. Zidan | 10545