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

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Digital Forensics and Watermarking (IWDW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10082))

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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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Acknowledgments

This work was supported in part by project supported by National Natural Science Foundation of China (Grant Nos. 61572182, 61370225), project supported by Hunan Provincial Natural Science Foundation of China (Grant No. 15JJ2007), and supported by the Scientific Research Plan of Hunan Provincial Science and Technology Department of China (2014FJ4161).

The authors thank Prof. Xiangui Kang from Sun Yat-sen University for providing the source code of CAGIF method.

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Authors and Affiliations

  1. School of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Le-Bing Zhang & Fei Peng

  2. College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410112, China

    Min Long

Authors
  1. Le-Bing Zhang
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  2. Fei Peng
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  3. Min Long
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Corresponding author

Correspondence to Fei Peng .

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Editors and Affiliations

  1. New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun Qing Shi

  2. Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

  3. University of Vigo, Vigo, Spain

    Fernando Perez-Gonzalez

  4. Chinese Academy of Sciences, Beijing, China

    Feng Liu

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Zhang, LB., Peng, F., Long, M. (2017). Source Camera Identification Based on Guided Image Estimation and Block Weighted Average. In: Shi, Y., Kim, H., Perez-Gonzalez, F., Liu, F. (eds) Digital Forensics and Watermarking. IWDW 2016. Lecture Notes in Computer Science(), vol 10082. Springer, Cham. https://doi.org/10.1007/978-3-319-53465-7_8

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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53464-0

  • Online ISBN: 978-3-319-53465-7

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