Technical Note

Identification Method for Digital Image Forgery and Filtering Region through Interpolation

Min Gu Hwang Ph.D.

Digital Scientific Imaging Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, 221 Huksuk-dong, Dongjak-ku, Seoul, Korea

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Dong Hwan Har Ph.D.,

Corresponding Author

Dong Hwan Har Ph.D.

Digital Scientific Imaging Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, 221 Huksuk-dong, Dongjak-ku, Seoul, Korea

Additional information and reprint requests:

Min-Gu Hwang, Ph.D.

Digital Scientific Imaging Laboratory

Graduate School of Advanced Imaging Science

Multimedia and Film

Chung-Ang University

221 Huksuk-dong, Dongjak-ku

Art Center, #103

Seoul

Korea

E-mail: [email protected]

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Min Gu Hwang Ph.D.,

Min Gu Hwang Ph.D.

Digital Scientific Imaging Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, 221 Huksuk-dong, Dongjak-ku, Seoul, Korea

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Dong Hwan Har Ph.D.,

Corresponding Author

Dong Hwan Har Ph.D.

Digital Scientific Imaging Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, 221 Huksuk-dong, Dongjak-ku, Seoul, Korea

Additional information and reprint requests:

Min-Gu Hwang, Ph.D.

Digital Scientific Imaging Laboratory

Graduate School of Advanced Imaging Science

Multimedia and Film

Chung-Ang University

221 Huksuk-dong, Dongjak-ku

Art Center, #103

Seoul

Korea

E-mail: [email protected]

Search for more papers by this author

First published: 03 June 2014

https://doi.org/10.1111/1556-4029.12507

Citations: 4

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Abstract

Because of the rapidly increasing use of digital composite images, recent studies have identified digital forgery and filtering regions. This research has shown that interpolation, which is used to edit digital images, is an effective way to analyze digital images for composite regions. Interpolation is widely used to adjust the size of the image of a composite target, making the composite image seem natural by rotating or deforming. As a result, many algorithms have been developed to identify composite regions by detecting a trace of interpolation. However, many limitations have been found in detection maps developed to identify composite regions. In this study, we analyze the pixel patterns of noninterpolation and interpolation regions. We propose a detection map algorithm to separate the two regions. To identify composite regions, we have developed an improved algorithm using minimum filer, Laplacian operation and maximum filters. Finally, filtering regions that used the interpolation operation are analyzed using the proposed algorithm.

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Volume59, Issue5

September 2014

Pages 1372-1385

Identification Method for Digital Image Forgery and Filtering Region through Interpolation

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Identification Method for Digital Image Forgery and Filtering Region through Interpolation

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