TY - JOUR
T1 - Camera identification of multi-format devices
AU - Taspinar, Samet
AU - Mohanty, Manoranjan
AU - Memon, Nasir
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/12
Y1 - 2020/12
N2 - Photo Response Non-Uniformity (PRNU) based source camera attribution is an effective method to determine an image or a video's origin camera. However, modern devices, especially smartphones, capture images and videos at different resolutions using the same sensor array, PRNU attribution can become ineffective as the camera fingerprint and query object can be misaligned. While capturing visual objects (either image or video), cameras may use different in-camera operations as well as they may use different parts of the sensor. In this paper, we investigate the problem of source camera attribution of a visual object by doing a thorough investigation of a comprehensive dataset, NYUAD Mixed Media Dataset. This investigation takes many factors into accounts, such as the fact that visual objects may have been captured using different resolution and aspect ratios. Furthermore, the visual objects may use different regions of the sensor, including the usage of boundary pixels for videos. Taking these various cases into account, we propose an efficient search which not only gives the state-of-the-art results but also performs significantly faster compared to existing methods.
AB - Photo Response Non-Uniformity (PRNU) based source camera attribution is an effective method to determine an image or a video's origin camera. However, modern devices, especially smartphones, capture images and videos at different resolutions using the same sensor array, PRNU attribution can become ineffective as the camera fingerprint and query object can be misaligned. While capturing visual objects (either image or video), cameras may use different in-camera operations as well as they may use different parts of the sensor. In this paper, we investigate the problem of source camera attribution of a visual object by doing a thorough investigation of a comprehensive dataset, NYUAD Mixed Media Dataset. This investigation takes many factors into accounts, such as the fact that visual objects may have been captured using different resolution and aspect ratios. Furthermore, the visual objects may use different regions of the sensor, including the usage of boundary pixels for videos. Taking these various cases into account, we propose an efficient search which not only gives the state-of-the-art results but also performs significantly faster compared to existing methods.
KW - Camera attribution
KW - Media forensics
KW - PRNU
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U2 - 10.1016/j.patrec.2020.10.010
DO - 10.1016/j.patrec.2020.10.010
M3 - Article
AN - SCOPUS:85095699101
SN - 0167-8655
VL - 140
SP - 288
EP - 294
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
ER -