Patch-based sensor pattern noise for camera source identification

Yang, Tan; Wang, Bo; Zhao, Mei; Kong, Xiangwei; Li, Ming

doi:10.1109/chinasip.2015.7230528

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Deng [3] proposed an auto white balance approximation but it has certain limitations to identify the source camera. A patch based approach for camera identification was proposed by Yue Tan [4] but it is not applicable for all kind of images. Dirik et al [6] argued that the location and shape of dust specks infornt of the imaging sensor is a useful fingerprint for source camera identification.…”

Section: Related Workmentioning

confidence: 99%

Source Camera Identification using Feature Extraction

Anujan¹

2016

IJERT

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The means and incentive to create digital image forgeries increased because of the increasing use of digital image, thus feature based source camera identification plays a crucial role in the authentication of digital images. The drawback of the conventional systems is the problem of unknown models. To rectify the disadvantage, camera model identification with unknown model was introduced but the accuracy level was found 28%. To increase the accuracy to an acceptable level, the proposed system was introduced. The new scheme consist of four stages: 1) feature extraction 2) unknown detection 3) unknown expansion 4) classification. In feature extraction, the input image is represented in 10 different formats and from each format 34 features are extracted, thus a total of 340 features are extracted from a single image. Then a KNN based unknown detection and a self training based unknown expansion is done. Finally classification is done using multi-class SVM with quadratic kernel. The experiments were carried out on Dresden image collection which confirms the effectiveness of the proposed system. The accuracy of the proposed system is found to be about 86%

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Section: Related Workmentioning

confidence: 99%

Source Camera Identification using Feature Extraction

Anujan¹

2016

IJERT

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“…In [1], a patch-based (PB) SPN is extracted from the image and then algorithm is implemented. Authors proposed a method based upon the detection of the dust particles [2].…”

Section: Review Processmentioning

confidence: 99%

To discover the dust patterns from image in source camera identification-A survey

Kaur¹,

Sharma²

2016

IOSR

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The source camera identification is the technique in which we identify the problems that affect the images which are taken with digital cameras or mobile phones. The images which are taken with the professional cameras like DSLR are of high quality, but when the dust particles or other noise parameters introduced in the capturing device then it leads to create the dust patterns on the image which is captured. When the dust particles stuck on the captured image it reduces the image quality. In this paper, various techniques are discussed in which various features are detected from the captured image.

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