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Blind biometric source sensor recognition using advanced PRNU fingerprints
2015
2015 23rd European Signal Processing Conference (EUSIPCO)
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The images under investigation, furthermore, show a strong correlation regarding their content, therefore we make use of different PRNU enhancements approaches based on weighting the PRNU depending on ...
These variations may have been caused by the usage of multiple sensors of the same model for the image acquisition. ...
Blind Camera Fingerprinting and Image Clustering First the Blind Camera Fingerprinting and Image Clustering (BCFAIC) technique was applied to the different subsets of the CASIA-Iris V4 database. ...
doi:10.1109/eusipco.2015.7362489
dblp:conf/eusipco/DebiasiU15
fatcat:fymts5q25bc67cd7skxkljddfu
Comparison of PRNU enhancement techniques to generate PRNU fingerprints for biometric source sensor attribution
2016
2016 4th International Conference on Biometrics and Forensics (IWBF)
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Identifying the source camera which acquired a given image using the cameras PRNU is a well established task in image forensics, known as camera or device identification. ...
In this paper we compare the use of a PRNU enhancement technique to the use of special uncorrelated images acquired with known biometric sensors in this clustering context. ...
identification of each images source camera without any prior knowledge of source. ...
doi:10.1109/iwbf.2016.7449674
dblp:conf/iwbf/DebiasiU16
fatcat:x4vbd5h7xbbpxpxtvemdcfthza
Techniques for a forensic analysis of the CASIA-IRIS V4 database
2015
3rd International Workshop on Biometrics and Forensics (IWBF 2015)
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performing a source device identification. ...
We apply an existing forensic technique and we propose several novel forensic techniques to establish a ground truth of how many sensors have been used to a acquire a digital image data set in a blind ...
set of images, enabling identification of each images source camera without any prior knowledge of source. ...
doi:10.1109/iwbf.2015.7110236
dblp:conf/iwbf/DebiasiU15
fatcat:bwgcsizfe5aklpirc2s53nc56u
K-unknown models detection through clustering in blind source camera identification
2018
IET Image Processing
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Source camera identification (SCI) is a forensic problem of mapping an image back to its source, often in relation to cybercrime. ...
Under such a circumstance, the conventional source detection techniques fail to identify the correct source, and falsely map the image to one of the accessible camera models. ...
[24] proposed a normalised cuts criterion for blind image clustering. ...
doi:10.1049/iet-ipr.2017.1142
fatcat:rhqfafa6znaalgd5cuzct7jcba
Blind Detection and Localization of Video Temporal Splicing Exploiting Sensor-Based Footprints
2018
2018 26th European Signal Processing Conference (EUSIPCO)
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In this paper, we tackle the problem of blind video temporal splicing detection leveraging PRNU-based source attribution. ...
Despite this approach has proved robust and efficient for images, exploiting PRNU in the video domain is still challenging. ...
Originally, it was used for image forensic tasks, like source identification or image forgery detection [6] , [7] . ...
doi:10.23919/eusipco.2018.8553511
dblp:conf/eusipco/MandelliBTCV18
fatcat:svcuntyw6rfvvedqyg6gyxoeze
Combining PRNU and noiseprint for robust and efficient device source identification
2020
EURASIP Journal on Information Security
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PRNU-based image processing is a key asset in digital multimedia forensics. ...
These include working on compressed and cropped images or estimating the camera PRNU pattern based on only a few images. ...
In future work we want to extend the proposed approach to improve PRNU-based image forgery detection and localization, and also to perform accurate blind image clustering, an important problem in multimedia ...
doi:10.1186/s13635-020-0101-7
fatcat:t4hpujvlorbhjkeptuce3fsc64
Combining PRNU and noiseprint for robust and efficient device source identification
[article]
2020
arXiv
pre-print
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PRNU-based image processing is a key asset in digital multimedia forensics. ...
These include working on compressed and cropped images, or estimating the camera PRNU pattern based on only a few images. ...
The U.S.Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. ...
arXiv:2001.06440v1
fatcat:uu35i6j6ubej5jsliwygecu2mq
Beyond PRNU: Learning Robust Device-Specific Fingerprint for Source Camera Identification
2022
Sensors
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Source-camera identification tools assist image forensics investigators to associate an image with a camera. ...
To address the PRNU's fragility issue, in recent years, deep learning-based data-driven approaches have been developed to identify source-camera models. ...
Blind-source identification techniques take advantage of the subtle traces left on the image by various modules involved in the image acquisition pipeline. ...
doi:10.3390/s22207871
fatcat:iodu5ktlwvbwln4sf7hatnjc74
Beyond PRNU: Learning Robust Device-Specific Fingerprint for Source Camera Identification
[article]
2021
arXiv
pre-print
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Source camera identification tools assist image forensic investigators to associate an image in question with a suspect camera. ...
In recent years, deep learning based approaches have been successful in identifying source camera models. ...
Moreover, the extracted PRNU pattern has the same pixel number as the original image, which incurs high computational and storage costs for source-oriented image clustering [19] [20] [21] . ...
arXiv:2111.02144v1
fatcat:qiiprg4zunbcrkgx2ketmhdzsa
Linear Filter Kernel Estimation Based on Digital Camera Sensor Noise
2017
IS&T International Symposium on Electronic Imaging Science and Technology
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We study linear filter kernel estimation from processed digital images under the assumption that the image's source camera is known. ...
The result is a simple yet accurate filter kernel estimation technique that is relatively independent of image content and that does not rely on hand-crafted parameter settings. ...
In the context of digital image forensics, camera sensor noise fingerprints have been successfully employed in camera identification [29] , camera-based blind image clustering [30] , and image manipulation ...
doi:10.2352/issn.2470-1173.2017.7.mwsf-332
fatcat:pa3mzu7tojedvjtsu2esmjkxzi
Extracting camera-based fingerprints for video forensics
2019
Computer Vision and Pattern Recognition
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Experiments show that methods based on video noiseprints perform well in major forensic tasks, such as camera model identification and video forgery localization, with no need of prior knowledge on the ...
Identifying which specific device or camera model took a video can help in authorship verification, but can be also a precious source of information for detecting a possible manipulation. ...
These include source identification and forgery localization in images [6, 7] and videos [32] . ...
dblp:conf/cvpr/CozzolinoPV19
fatcat:xd7qpfmvt5e43eysyg5bwcmbt4
Determining Image Sensor Temperature Using Dark Current
[article]
2019
arXiv
pre-print
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This photo-response non-uniformity (PRNU) noise has shown to be effective but ignores knowledge of image sensor output under equilibrium states without excitation (dark current). ...
We hypothesise that DSN is not only a viable method for forensic identification but, through proper analysis of the thermal component, can lead to insights regarding the specific temperature at which an ...
Sensor Pattern Noise (SPN) methods for solving the blind source camera identification problem has already been shown to be a valuable tool for both insurance providers and law enforcement. ...
arXiv:1901.02113v1
fatcat:rjk75pxqczd67bb4yzaqi37evu
Source Identification of Videos Transmitted in Lossy Wireless Networks
2017
IJIREEICE
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matching and our proposed work based on Gaussian Mixture Model matching. ...
Experiment test was conducted with 20 test each on 8 videos of eight wireless cameras taking randomly 5 frames of the video to be tested using Sensor Pattern Noise based on correlation based coeffient ...
The image source identification methods can be easily adopted directly for video source identification. ...
doi:10.17148/ijireeice.2017.5552
fatcat:5o5k4uiin5dtfiomtcjkaxr6ni
Digital image forgery detection techniques: a survey
2016
ACCENTS Transactions on Information Security
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They then proposed a geometry-based image model that reveals the differences. For source identification, the method extracts the geometry features based on the rigid body moments. ...
FPN is an offset, while PRNU is a gain. Therefore, the primary source of pattern noise remaining in nature images may be PRNU. Two sources contribute to PRNU. ...
doi:10.19101/tis.2017.25003
fatcat:vyi63ahmrvfeljjpqqiooxy334
Source Camera Verification from Strongly Stabilized Videos
[article]
2020
arXiv
pre-print
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Image stabilization performed during imaging and/or post-processing poses one of the most significant challenges to photo-response non-uniformity based source camera attribution from videos. ...
Hence, successful attribution requires the inversion of these transformations in a blind manner. ...
The PRNU of a sensor is proven to be a viable identifier for source attribution, and it has been successfully utilized for identification and verification of the source of digital media. ...
arXiv:1912.05018v4
fatcat:l7vc2nz3cfadhgqm7vfvyy7lru
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