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Defocused Image Splicing Localization by Distinguishing Multiple Cues between Raw Naturally Blur and Artificial Blur

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Digital Forensics and Watermarking (IWDW 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12617))

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Abstract

Splicing is one common type of forgery that maliciously changes the image contents. To make the forged image more realistic, blurring operations may be conducted to partial image regions or splicing edges to promise visual consistency. Revealing the blurring inconsistency among the whole image regions contributes to the splicing detection. However, for the defocused image already containing blur inconsistency, the existing methods cannot work well. Splicing detection and localization in defocused image is a challenging problem. In this paper, we overcome this problem by distinguishing multiple cues between raw naturally blur and artificial blur. Firstly, after the overlapped image blocks partition, three kinds of feature sets are extracted based on posterior probability map, noise histogram and derivative co-occurrence matrix. Then, an effective classifier is trained to determine the blur property of each pixel. Finally, a localization map refinement is proposed by fusing color segmentation probability map to improve the quality of the locating result. Experimental results demonstrate that the proposed method is very effective to detect splicing for the defocused images. The localization accuracy also outperforms the existing methods.

This work was supported in part by the National Key Research and Development of China (2018YFC0807306), National NSF of China (U1936212, 61672090), and Beijing Fund-Municipal Education Commission Joint Project (KZ202010015023).

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Authors and Affiliations

  1. Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China

    Xiaoyu Zhao, Yakun Niu, Rongrong Ni & Yao Zhao

  2. Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, 100044, China

    Xiaoyu Zhao, Yakun Niu, Rongrong Ni & Yao Zhao

Authors
  1. Xiaoyu Zhao
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  2. Yakun Niu
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  3. Rongrong Ni
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  4. Yao Zhao
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Corresponding author

Correspondence to Rongrong Ni .

Editor information

Editors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Xianfeng Zhao

  2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA

    Yun-Qing Shi

  3. Department of Information Engineering, University of Florence, Florence, Italy

    Alessandro Piva

  4. School of Cybersecurity, Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

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Zhao, X., Niu, Y., Ni, R., Zhao, Y. (2021). Defocused Image Splicing Localization by Distinguishing Multiple Cues between Raw Naturally Blur and Artificial Blur. In: Zhao, X., Shi, YQ., Piva, A., Kim, H.J. (eds) Digital Forensics and Watermarking. IWDW 2020. Lecture Notes in Computer Science(), vol 12617. Springer, Cham. https://doi.org/10.1007/978-3-030-69449-4_12

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  • DOI: https://doi.org/10.1007/978-3-030-69449-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69448-7

  • Online ISBN: 978-3-030-69449-4

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