Forgery detection in digital images by multi-scale noise estimation.
A complex processing chain is applied from the moment a raw image is acquired until the final image is obtained. This process transforms the originally Poisson-distributed noise into a complex noise model. Noise inconsistency analysis is a rich source for forgery detection, as forged regions have li...
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| Otros Autores: | , , |
| Formato: | article |
| Lenguaje: | inglés |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2313-433X/7/7/119 https://hdl.handle.net/20.500.12008/46073 |
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| _version_ | 1868890123458838528 |
|---|---|
| author | Gardella, Marina |
| author2 | Musé, Pablo Morel, Jean-Michel Colom, Miguel |
| author2_role | author author author |
| author_browse | Colom, Miguel Gardella, Marina Morel, Jean-Michel Musé, Pablo |
| author_facet | Gardella, Marina Musé, Pablo Morel, Jean-Michel Colom, Miguel |
| author_role | author |
| collection | COLIBRI |
| dc.contributor.none.fl_str_mv | Gardella Marina, Université Paris-Saclay, France. Musé Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería. Morel Jean-Michel, Université Paris-Saclay, France. Colom Miguel, Université Paris-Saclay, France. |
| dc.creator.none.fl_str_mv | Gardella, Marina Musé, Pablo Morel, Jean-Michel Colom, Miguel |
| dc.date.none.fl_str_mv | 2021 2024-09-26T15:30:29Z 2024-09-26T15:30:29Z |
| dc.format.none.fl_str_mv | 16 p. application/pdf |
| dc.identifier.none.fl_str_mv | Gardella, M., Musé, P., Morel, J. y otros. "Forgery detection in digital images by multi-scale noise estimation". Journal of Imaging. [en línea]. 2021, vol. 7, no. 7, pp. 1-16. DOI: 10.3390/jimaging7070119. 2313-433X https://www.mdpi.com/2313-433X/7/7/119 https://hdl.handle.net/20.500.12008/46073 10.3390/jimaging7070119 |
| dc.language.none.fl_str_mv | en eng |
| dc.publisher.none.fl_str_mv | MDPI |
| dc.relation.none.fl_str_mv | Journal of Imaging, vol. 7, no. 7, jul 2021, pp. 1-16. |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess Licencia Creative Commons Atribución (CC - By 4.0) |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.none.fl_str_mv | Blind estimation Forged image detection Heatmap JPEG Noise level function |
| dc.title.none.fl_str_mv | Forgery detection in digital images by multi-scale noise estimation. |
| dc.type.none.fl_str_mv | Artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | A complex processing chain is applied from the moment a raw image is acquired until the final image is obtained. This process transforms the originally Poisson-distributed noise into a complex noise model. Noise inconsistency analysis is a rich source for forgery detection, as forged regions have likely undergone a different processing pipeline or out-camera processing. We propose a multi-scale approach, which is shown to be suitable for analyzing the highly correlated noise present in JPEG-compressed images. We estimate a noise curve for each image block, in each color channel and at each scale. We then compare each noise curve to its corresponding noise curve obtained from the whole image by counting the percentage of bins of the local noise curve that are below the global one. This procedure yields crucial detection cues since many forgeries create a local noise deficit. Our method is shown to be competitive with the state of the art. It outperforms all other methods when evaluated using the MCC score, or on forged regions large enough and for colorization attacks, regardless of the evaluation metric. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | anni_8af2dd60505bc3aaf8db4e22199d9d49 |
| identifier_str_mv | Gardella, M., Musé, P., Morel, J. y otros. "Forgery detection in digital images by multi-scale noise estimation". Journal of Imaging. [en línea]. 2021, vol. 7, no. 7, pp. 1-16. DOI: 10.3390/jimaging7070119. 2313-433X 10.3390/jimaging7070119 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | anni |
| network_name_str | oai-lr-anni |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/46073 |
| publishDate | 2021 |
| publishDateSort | 2021 |
| publisher.none.fl_str_mv | MDPI |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | Licencia Creative Commons Atribución (CC - By 4.0) |
| spelling | Forgery detection in digital images by multi-scale noise estimation.Gardella, MarinaMusé, PabloMorel, Jean-MichelColom, MiguelBlind estimationForged image detectionHeatmapJPEGNoise level functionA complex processing chain is applied from the moment a raw image is acquired until the final image is obtained. This process transforms the originally Poisson-distributed noise into a complex noise model. Noise inconsistency analysis is a rich source for forgery detection, as forged regions have likely undergone a different processing pipeline or out-camera processing. We propose a multi-scale approach, which is shown to be suitable for analyzing the highly correlated noise present in JPEG-compressed images. We estimate a noise curve for each image block, in each color channel and at each scale. We then compare each noise curve to its corresponding noise curve obtained from the whole image by counting the percentage of bins of the local noise curve that are below the global one. This procedure yields crucial detection cues since many forgeries create a local noise deficit. Our method is shown to be competitive with the state of the art. It outperforms all other methods when evaluated using the MCC score, or on forged regions large enough and for colorization attacks, regardless of the evaluation metric.Este trabajo fue financiado por la beca de doctorado de la Región de París de la Región Île-de-France, la Red Internacional de Verificación de Datos (IFCN) y la Agence France Presse (AFP) a través del proyecto Enhancing Visual Forensics (Envisu4), el DGA Defals challenge n° ANR-16-DEFA-0004-01, MENRT y la Fundación Matemática Jacques Hadamard.MDPIGardella Marina, Université Paris-Saclay, France.Musé Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.Morel Jean-Michel, Université Paris-Saclay, France.Colom Miguel, Université Paris-Saclay, France.2024-09-26T15:30:29Z2024-09-26T15:30:29Z2021Artículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion16 p.application/pdfGardella, M., Musé, P., Morel, J. y otros. "Forgery detection in digital images by multi-scale noise estimation". Journal of Imaging. [en línea]. 2021, vol. 7, no. 7, pp. 1-16. DOI: 10.3390/jimaging7070119.2313-433Xhttps://www.mdpi.com/2313-433X/7/7/119https://hdl.handle.net/20.500.12008/4607310.3390/jimaging7070119reponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaenengJournal of Imaging, vol. 7, no. 7, jul 2021, pp. 1-16.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución (CC - By 4.0)oai:colibri.udelar.edu.uy:20.500.12008/460732026-04-14T10:15:59Z |
| spellingShingle | Forgery detection in digital images by multi-scale noise estimation. Gardella, Marina Blind estimation Forged image detection Heatmap JPEG Noise level function |
| status_str | publishedVersion |
| title | Forgery detection in digital images by multi-scale noise estimation. |
| title_full | Forgery detection in digital images by multi-scale noise estimation. |
| title_fullStr | Forgery detection in digital images by multi-scale noise estimation. |
| title_full_unstemmed | Forgery detection in digital images by multi-scale noise estimation. |
| title_short | Forgery detection in digital images by multi-scale noise estimation. |
| title_sort | Forgery detection in digital images by multi-scale noise estimation. |
| topic | Blind estimation Forged image detection Heatmap JPEG Noise level function |
| url | https://www.mdpi.com/2313-433X/7/7/119 https://hdl.handle.net/20.500.12008/46073 |