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Forensics feature analysis in quaternion wavelet domain for distinguishing photographic images and computer graphics

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Abstract

In this paper, a novel set of features based on Quaternion Wavelet Transform (QWT) is proposed for digital image forensics. Compared with Discrete Wavelet Transform (DWT) and Contourlet Wavelet Transform (CWT), QWT produces the parameters, i.e., one magnitude and three angles, which provide more valuable information to distinguish photographic (PG) images and computer generated (CG) images. Some theoretical analysis are done and comparative experiments are made. The corresponding results show that the proposed scheme achieves 18 percents’ improvements on the detection accuracy than Farid’s scheme and 12 percents than Özparlak’s scheme. It may be the first time to introduce QWT to image forensics, but the improvements are encouraging.

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Acknowledgments

This work was jointly supported by the National Natural Science Foundation of China (Grant No. 61272421, 61103141, 61232016, 61173141, 61103201, 61402235), the Natural Science Foundation of Jiangsu Higher Education Institutions of China (Grant No. 12KJB520006), the Priority Academic Program Development of Jiangsu Higher Education Institutions, Jiangsu Government Scholarship for Overseas Studies and CICAEET.

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Authors and Affiliations

  1. Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, China

    Jinwei Wang & Ting Li

  2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, People’s Republic of China

    Jinwei Wang & Ting Li

  3. New Jersey Institute of Technology, Newark, NJ, USA

    Yun-Qing Shi & Jingyu Ye

  4. Central Research Institute, Huawei Technologies, Beijing, 100085, People’s Republic of China

    Shiguo Lian

Authors
  1. Jinwei Wang
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  2. Ting Li
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  3. Yun-Qing Shi
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  4. Shiguo Lian
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  5. Jingyu Ye
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Correspondence to Jinwei Wang.

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Wang, J., Li, T., Shi, YQ. et al. Forensics feature analysis in quaternion wavelet domain for distinguishing photographic images and computer graphics. Multimed Tools Appl 76, 23721–23737 (2017). https://doi.org/10.1007/s11042-016-4153-0

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  • DOI: https://doi.org/10.1007/s11042-016-4153-0

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