A Robust Seam Carving Forgery Detection Approach by Three-Element Joint Density of Difference Matrix

  • Wenwu Gu
  • Gaobo YangEmail author
  • Dengyong Zhang
  • Ming Xia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10603)


Seam carving is a popular content-aware image retargeting technique. However, it can also be used for malicious purposes such as object removal. In this paper, a robust blind forensics approach is proposed for seam-carved forgery detection. Since insignificant pixels along seams are removed for image resizing, the spatial neighborhood relations among pixels will be significantly changed, especially in smooth regions. Thus, joint density is exploited to model the change of spatially adjacent pixels’ distribution caused by seam carving, even in the case of low scaling ratios. Specifically, three-element joint density of difference matrix is computed to form general forensics features (GTJD). The GTJD features are combined with existing energy and noise features exacted in LBP domain for classification. Experimental results show that the proposed approach achieves better accuracies for both uncompressed images and JPEG images with different scaling ratios.


Blind image forensic Content-aware image retargeting Seam carving Difference matrix Three-element joint density 



This work is supported in part by the National Natural Science Foundation of China (61572183, 61379143, 61672222), the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) under grant 20120161110014, the Priority Academic Program Development of Jiangsu Higer Education Institutions (PAPD) and Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Wenwu Gu
    • 1
  • Gaobo Yang
    • 1
    Email author
  • Dengyong Zhang
    • 1
  • Ming Xia
    • 1
  1. 1.School of Information Science and EngineeringHunan UniversityChangshaChina

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