De-identifying facial images using singular value decomposition and projections

P. Chriskos, Olga Zoidi, Anastasios Tefas, Ioannis Pitas

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)
217 Downloads (Pure)

Abstract

In this paper, two methods are presented that manipulate images to hinder automatic face identification. They partly degrade image quality, so that humans can identify the persons in a scene, while face identification algorithms fail to do so. The approaches used involve: a) singular value decomposition (SVD) and b) image projections on hyperspheres. Simulation experiments verify that these methods reduce the percentage of correct face identification rate by over 90 %. Additionally, the final image is not degraded beyond recognition by humans, in contrast with the majority of other de-identification methods.
Original languageEnglish
Pages (from-to)3435–3468
Number of pages34
JournalMultimedia Tools and Applications
Volume76
Issue number3
Early online date5 Nov 2016
DOIs
Publication statusPublished - Feb 2017

Keywords

  • Face de-idenification
  • Privacy protection
  • Singular value decomposition
  • Projections on hyperspheres

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