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Source camera identification from image texture features

delete2016-09-01
delete45
PRE
AI
B
Bingchao Xu
X
Xiaofeng Wang *
X
Xiaorui Zhou
J
Jianghuan Xi
S
Shangping Wang
DOI:10.1016/j.neucom.2016.05.012delete
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Abstract

Abstract

En 中文
Source camera identification enables forensic investigator to discover the probable source model that are employed to acquire the image under investigation. It is important whenever digital content is presented as a silent witness. In this paper, we present a source camera identification method via linage texture features that are extracted from well selected color model and color channel. Except to distinguish source camera models from images whatever they are captured via same or different brand cameras, the main contributions of the proposed method are as follows: (1) It can distinguish imaging device individuals from images even if they are taken by using same brand and model of devices. (2) It is robust for content preserving manipulations or geometric distortions, such as JEPG compression, adding noise, and rotation and scaling. The experimental results demonstrate that the performance of the proposed method is satisfactory. Compared with the state-of-the-art methods, the proposed method is superior in both detection accuracy and robustness. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
Source camera identification
Local Binary Pattern (LBP)
Local Phase Quantization (LPQ)
Support vector machine (SVM)
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Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

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