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Erschienen in:
A Multi-purpose Image Counter-anti-forensic Method Using Convolutional Neural Networks Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Source Camera Identification Based on Guided Image Estimation and Block Weighted Average

verfasst von : Le-Bing Zhang, Fei Peng, Min Long

Erschienen in: Digital Forensics and Watermarking

Verlag: Springer International Publishing

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Abstract

Sensor pattern noise (SPN) has been widely used in source camera identification. However, the SPN extracted from natural image may be contaminated by its content and eventually introduce side effect to the identification accuracy. In this paper, an effective source camera identification scheme based on guided image estimation and block weighted average is proposed. Before the SPN extraction, an adaptive SPN estimator based on image content is implemented to reduce the influence of image scene and improve the quality of the SPN. Furthermore, a novel camera reference SPN construction method is put forward by using some ordinary images, instead of the blue sky images in previous schemes, and a block weighted average approach is used to suppress the influence of the image scenes in the reference SPN. Experimental results and analysis indicate that the proposed method can effectively identify the source of the natural image, especially in actual forensics environment with a small number of images.

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Vorheriges Kapitel Using Benford’s Law Divergence and Neural Networks for Classification and Source Identification of Biometric Images
Nächstes Kapitel Recapture Image Forensics Based on Laplacian Convolutional Neural Networks
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Metadaten
Titel
Source Camera Identification Based on Guided Image Estimation and Block Weighted Average
verfasst von
Le-Bing Zhang
Fei Peng
Min Long
Copyright-Jahr
2017
Buch
Digital Forensics and Watermarking

Print ISBN: 978-3-319-53464-0

Electronic ISBN: 978-3-319-53465-7

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-53465-7_8