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Symmetry 2019, 11(1), 83;

Hybrid Image-Retrieval Method for Image-Splicing Validation

Department of Digital Contents, Sejong University, Seoul 05006, Korea
Department of Software, Sejong University, Seoul 05006, Korea
Department of Information and Communication Engineering, Chosun University, Gwangju 61452, Korea
Department of Computer Education, Sungkyunkwan University, Seoul 03063, Korea
Author to whom correspondence should be addressed.
Received: 22 November 2018 / Revised: 9 January 2019 / Accepted: 10 January 2019 / Published: 14 January 2019
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Recently, the task of validating the authenticity of images and the localization of tampered regions has been actively studied. In this paper, we go one step further by providing solid evidence for image manipulation. If a certain image is proved to be the spliced image, we try to retrieve the original authentic images that were used to generate the spliced image. Especially for the image retrieval of spliced images, we propose a hybrid image-retrieval method exploiting Zernike moment and Scale Invariant Feature Transform (SIFT) features. Due to the symmetry and antisymmetry properties of the Zernike moment, the scaling invariant property of SIFT and their common rotation invariant property, the proposed hybrid image-retrieval method is efficient in matching regions with different manipulation operations. Our simulation shows that the proposed method significantly increases the retrieval accuracy of the spliced images. View Full-Text
Keywords: image splicing; localization; image retrieval; Zernike moment; SIFT image splicing; localization; image retrieval; Zernike moment; SIFT

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Pham, N.T.; Lee, J.-W.; Kwon, G.-R.; Park, C.-S. Hybrid Image-Retrieval Method for Image-Splicing Validation. Symmetry 2019, 11, 83.

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