| Full text | |
| Author(s): |
Pomari, Thales
;
Ruppert, Guillherme
;
Rezende, Edmar
;
Rocha, Anderson
;
Carvalho, Tiago
;
IEEE
Total Authors: 6
|
| Document type: | Journal article |
| Source: | 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP); v. N/A, p. 5-pg., 2018-01-01. |
| Abstract | |
Fake news and deep fakes have been making social and mainstream media headlines. At the same time, engaged scientists strive for finding ways to detect forgeries and suspicious manipulations using even the subtlest clues. In this vein, this work proposes a new method for detecting photographic splicing by bringing together the high representation power of Illuminant Maps and Convolutional Neural Networks as a way of learning directly from available training data the most important hints of a forgery. This work propose a method that eliminates the laborious feature engineering process, allow locate forgery region and yields a classification accuracy of more than 96%, outperforming state-of-the-art methods in different datasets. The potential uses of the proposed method is further highlighted by analyzing some suspicious real-world photographs that recently broke the news. (AU) | |
| FAPESP's process: | 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/12631-6 - Developing and Spreading Methods and Tools for Digital Forensics |
| Grantee: | Tiago Jose de Carvalho |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 18/00858-9 - Associating illumination inconsistencies and deep learning methods to detect image splicing |
| Grantee: | Thales Augusto Paletti Pomari |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |