“A Patch Analysis Approach for Seam-Carved Image Detection” by Wei, Lin, Wu and Kang

  • ©Jyh-Da Wei, Yu-Ju Lin, Yi-Jing Wu, and Li-Wei Kang

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Entry Number: 06

Title:

    A Patch Analysis Approach for Seam-Carved Image Detection

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Abstract:


    Seam carving is a content-aware image resizing method [Shamir and Avidan 2007], which assigns Sobel-operator-based energy to each pixel and describes seams as the eight-connected paths of pixels. Successive removal of the optimal seams, i.e., those seams with the lowest sum of energy, allows reduction in image size. Pixels with lower energy are generally removed earlier; implying that (1) the modifications to the image are difficult to identify and (2) low energy can be deliberately assigned to particular objects so that they can be removed from the image. These two observations reveal that, although difficult, it is important to design a seam carving detection method.

References:


    1. Fillion, C., and Sharma, G. 2010. Detecting content adaptive scaling of images for forensic applications. In Proc. SPIE: Media Forensics and Security, vol. 7541, 36–47.
    2. Sarkar, A., Nataraj, L., and Manjunath, B. S. 2009. Detection of seam carving and localization of seam insertions in digital images. In Proc. 11th ACM workshop on Multimedia and security, 107–116.
    3. Shamir, A., and Avidan, S. 2007. Seam carving for content aware image resizing. ACM Transactions on Graphics 26, 3, 107–216.


Acknowledgements:


    This work was supported in part by the Republic of China National Science Council under the Grants NSC 101-2221-E-182-073.


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