Recognizing different kinds of modifications and identifying the altered portions of the face region have been the main focus of recent developments in face image manipulation detection. In actual applications, the ability to restore the facial region after modification localization would be highly helpful, but this was not addressed in earlier studies. This research utilizes integer wavelet transform (IWT) coefficients to produce recovery information from the face region and watermarking-based technique for incorporating the generated data into the cover face image. Three distinct algorithms have been proposed for producing the recovery data, and the one demonstrating superior performance, specifically IWT (cdf 3.5), is employed within main algorithms. The novelty of the suggested technique stems from its integration of an IWT-based recovery method, along with the manipulation detection process, which has not been showcased in prior research studies. The main contributions of the suggested algorithm include its efficiency to precisely identify altered blocks within the facial area and to reinstate the unaltered version when modifications are present. The advantage of the proposed algorithm is demonstrated through the comparisons with earlier methods where it can be used in digital art to ensure the originality, integrity, and security of facial images. The practical applications include various fields such as forensic investigations, digital image authentication, online safety, content moderation, medical imaging, security systems, entertainment, privacy protection, historical documentation, The limitation of the proposed algorithm is the restricted embedding capacity. The future researches can be conducted in different directions such as enhancing the embedding capacity, implementing a real-time detection system for live video streams, and investigating the main requirements for efficient algorithm's execution on hardware devices.
تاريخ النشر
06/04/2024
الناشر
Mathematical Modelling of Engineering Problems, 2024,
أ د خميس عواد زيدان | Khamis A. Zidan | 10949