| bibtype |
J -
Journal Article
|
| ARLID |
0326282 |
| utime |
20240103191810.6 |
| mtime |
20090622235959.9 |
| WOS |
000268403800008 |
| DOI |
10.1016/j.imavis.2009.02.001 |
| title
(primary) (eng) |
Using noise inconsistencies for blind image forensics |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0256733 |
| ISSN |
0262-8856 |
| title
|
Image and Vision Computing |
| volume_id |
27 |
| volume |
10 (2009) |
| page_num |
1497-1503 |
| publisher |
|
|
| title
(cze) |
Použití šumových nehomogenit při pasivním ověřování pravosti fotografií |
| keyword |
Image forensics |
| keyword |
Digital forgery |
| keyword |
Image tampering |
| keyword |
Image segmentation |
| author
(primary) |
| ARLID |
cav_un_auth*0101189 |
| name1 |
Saic |
| name2 |
Stanislav |
| institution |
UTIA-B |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0206076 |
| name1 |
Mahdian |
| name2 |
Babak |
| institution |
UTIA-B |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA102/08/0470 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239565 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
A commonly used tool to conceal the traces of tampering is the addition of locally random noise to the altered image regions. The noise degradation is the main cause of failure of many active or passive image forgery detection methods. The amount of noise is uniform across the entire authentic image. Adding locally random noise may cause inconsistencies in the image’s noise. Therefore, the detection of various noise levels in an image may signify tampering. In this paper, we propose a novel method capable of dividing an investigated image into various partitions with homogenous noise levels. In other words, we introduce a segmentation method detecting changes in noise level. We assume the additive white Gaussian noise. Several examples are shown to demonstrate the proposed method’s output. An extensive quantitative measure of the efficiency of the noise estimation part as a function of different noise standard deviations, region sizes and various JPEG compression qualities is proposed as well. |
| abstract
(cze) |
Obvyklý způsob, kterým se zakrývá úprava fotografií je přidání aditivního šumu. Přítomnost šumu znesnadňuje detekci těchto úprav.Avšak přidání lokálního šumu může způsobit nespojitosti šumu obrazu. V článku je navržena nová metoda, která je umožňuje rozdělení obrazu na části s homogením šumem. Na řadě experimentů je demonstrována účinnost metody a její závislost na JPEG komprimaci. |
| reportyear |
2010 |
| RIV |
IN |
| permalink |
http://hdl.handle.net/11104/0173430 |
| mrcbT16-f |
1.767 |
| mrcbT16-g |
0.286 |
| mrcbT16-h |
6.7 |
| mrcbT16-i |
0.00782 |
| mrcbT16-j |
0.592 |
| mrcbT16-k |
2926 |
| mrcbT16-l |
161 |
| mrcbT16-q |
75 |
| mrcbT16-s |
1.254 |
| mrcbT16-y |
33.93 |
| mrcbT16-x |
2.48 |
| arlyear |
2009 |
| mrcbU34 |
000268403800008 WOS |
| mrcbU63 |
cav_un_epca*0256733 Image and Vision Computing 0262-8856 1872-8138 Roč. 27 č. 10 2009 1497 1503 Elsevier |
|