| Texto completo | |
| Autor(es): |
Brogan, Joel
;
Bestagini, Paolo
;
Bharati, Aparna
;
Pinto, Allan
;
Moreira, Daniel
;
Bowyer, Kevin
;
Flynn, Patrick
;
Rocha, Anderson
;
Scheirer, Walter
;
IEEE
Número total de Autores: 10
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP); v. N/A, p. 5-pg., 2017-01-01. |
| Resumo | |
As image tampering becomes ever more sophisticated and commonplace, the need for image forensics algorithms that can accurately and quickly detect forgeries grows. In this paper, we revisit the ideas of image querying and retrieval to provide clues to better localize forgeries. We propose a method to perform large-scale image forensics on the order of one million images using the help of an image search algorithm and database to gather contextual clues as to where tampering may have taken place. In this vein, we introduce five new strongly invariant image comparison methods and test their effectiveness under heavy noise, rotation, and color space changes. Lastly, we show the effectiveness of these methods compared to passive image forensics using Nimble [1], a new, state-of-the-art dataset from the National Institute of Standards and Technology (NIST). (AU) | |
| Processo FAPESP: | 15/19222-9 - DejaVu: análise forense de mídias sociais para interpretação de eventos criminais |
| Beneficiário: | Anderson de Rezende Rocha |
| Modalidade de apoio: | Bolsas no Exterior - Pesquisa |