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Pattern Analysis and Applications

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30.03.2017 | Industrial and Commercial Application

New dissimilarity measures for image phylogeny reconstruction

verfasst von: Filipe Costa, Alberto Oliveira, Pasquale Ferrara, Zanoni Dias, Siome Goldenstein, Anderson Rocha

Erschienen in: Pattern Analysis and Applications | Ausgabe 4/2017

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Abstract

Image phylogeny is the problem of reconstructing the structure that represents the history of generation of semantically similar images (e.g., near-duplicate images). Typical image phylogeny approaches break the problem into two steps: (1) estimating the dissimilarity between each pair of images and (2) reconstructing the phylogeny structure. Given that the dissimilarity calculation directly impacts the phylogeny reconstruction, in this paper, we propose new approaches to the standard formulation of the dissimilarity measure employed in image phylogeny, aiming at improving the reconstruction of the tree structure that represents the generational relationships between semantically similar images. These new formulations exploit a different method of color adjustment, local gradients to estimate pixel differences and mutual information as a similarity measure. The results obtained with the proposed formulation remarkably outperform the existing counterparts in the literature, allowing a much better analysis of the kinship relationships in a set of images, allowing for more accurate deployment of phylogeny solutions to tackle traitor tracing, copyright enforcement and digital forensics problems.

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In our experiments, we have used the \(3 \times 3\) Sobel kernel. We performed some exploratory tests with other kernel sizes (e.g., \(3 \times 3\), \(5 \times 5\) and \(7 \times 7\)) but their performance was similar for the problem herein.

A topology refers to the form of the trees in a forest. For instance, Fig. 1 depicts two different topologies for the set of images present on its left side.

http://www.imagemagick.org/script/index.php.

http://migre.me/vTYN7 (secure shortened link).

For cases with \(n = 100\) images, the initial branching has \(n - 1 = 99\) edges. For creating a forest \({\mathcal {F}}\) where \(|{\mathcal {F}}| = 10\) trees, the number of total edges is \(n - |{\mathcal {F}}| = 100 - 10 = 90\).

http://migre.me/vTYLt (secure shortened link).

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Titel: New dissimilarity measures for image phylogeny reconstruction
verfasst von: Filipe Costa
Alberto Oliveira
Pasquale Ferrara
Zanoni Dias
Siome Goldenstein
Anderson Rocha
Publikationsdatum: 30.03.2017
Verlag: Springer London
Erschienen in: Pattern Analysis and Applications / Ausgabe 4/2017
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-017-0616-9

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