Sachin Sharma1,2,*, Brajesh Kumar Singh3, Hitendra Garg2
CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4691-4708, 2025, DOI:10.32604/cmc.2025.061252
- 06 March 2025
Abstract Image tampering detection and localization have emerged as a critical domain in combating the pervasive issue of image manipulation due to the advancement of the large-scale availability of sophisticated image editing tools. The manual forgery localization is often reliant on forensic expertise. In recent times, machine learning (ML) and deep learning (DL) have shown promising results in automating image forgery localization. However, the ML-based method relies on hand-crafted features. Conversely, the DL method automatically extracts shallow spatial features to enhance the accuracy. However, DL-based methods lack the global co-relation of the features due to this… More >
Login
Register
