Hybrid Image-Retrieval Method for Image-Splicing Validation
AbstractRecently, 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
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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.
Pham NT, Lee J-W, Kwon G-R, Park C-S. Hybrid Image-Retrieval Method for Image-Splicing Validation. Symmetry. 2019; 11(1):83.Chicago/Turabian Style
Pham, Nam T.; Lee, Jong-Weon; Kwon, Goo-Rak; Park, Chun-Su. 2019. "Hybrid Image-Retrieval Method for Image-Splicing Validation." Symmetry 11, no. 1: 83.
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