Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Toward image phylogeny forests: Automatically recovering semantically similar image relationships
Author: Dias, Z
Goldenstein, S
Rocha, A
Abstract: In the past few years, several near-duplicate detection methods appeared in the literature to identify the cohabiting versions of a given document online. Following this trend, there are some initial attempts to go beyond the detection task, and look into the structure of evolution within a set of related images overtime. In this paper, we aim at automatically identify the structure of relationships underlying the images, correctly reconstruct their past history and ancestry information, and group them in distinct trees of processing history. We introduce a new algorithm that automatically handles sets of images comprising different related images, and outputs the phylogeny trees (also known as a forest) associated with them. Image phylogeny algorithms have many applications such as finding the first image within a set posted online (useful for tracking copyright infringement perpetrators), hint at child pornography content creators, and narrowing down a list of suspects for online harassment using photographs. (c) 2013 Elsevier Ireland Ltd. All rights reserved.
Subject: Image phylogeny
Phylogeny trees
Kinship analysis
Digital forensics
Country: Irlanda
Editor: Elsevier Ireland Ltd
Citation: Forensic Science International. Elsevier Ireland Ltd, v. 231, n. 41699, n. 178, n. 189, 2013.
Rights: fechado
Identifier DOI: 10.1016/j.forsciint.2013.05.002
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.