De-Identifying Facial Images Using Singular Value Decomposition

P. Chriskos; O. Zoidi; Anastasios Tefas; Ioannis Pitas

doi:10.1109/MIPRO.2014.6859757

De-Identifying Facial Images Using Singular Value Decomposition

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

Department of Electrical & Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

2 Citations (Scopus)

256 Downloads (Pure)

Abstract

In this paper, a method is proposed that manipulates images in a manner that hinders face recognition by automatic recognition algorithms. The purpose of this method, is to partly degrade image quality, so that humans can identify the person
or persons in a scene, while common classification algorithms fail to do so. The approach used to achieve this involves the use of singular value decomposition (SVD). From experiments it can be concluded that, the method reduces the percentage of correct classification rate by over 90% . In addition, the final image is
not degraded beyond recognition by humans.

Original language	English
Title of host publication	2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014)
Subtitle of host publication	Proceedings of a meeting held 26-30 May 2014, Opatija, Croatia
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1240-1245
Number of pages	6
ISBN (Electronic)	9789532330816
ISBN (Print)	9781479956579
DOIs	https://doi.org/10.1109/MIPRO.2014.6859757
Publication status	Published - Sep 2014
Event	IEEE International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) - oPATIJA/aBBAZIA, Croatia Duration: 30 May 2014 → 3 Jun 2014

Conference

Conference	IEEE International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
Country/Territory	Croatia
City	oPATIJA/aBBAZIA
Period	30/05/14 → 3/06/14

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10.1109/MIPRO.2014.6859757

Ioannis Pitas - De-identifying facial images using projections on hyperspheres - 2015
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at 10.1109/MIPRO.2014.6859757. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 1.24 MB

Cite this

Chriskos, P., Zoidi, O., Tefas, A., & Pitas, I. (2014). De-Identifying Facial Images Using Singular Value Decomposition. In 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014): Proceedings of a meeting held 26-30 May 2014, Opatija, Croatia (pp. 1240-1245). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/MIPRO.2014.6859757

Chriskos, P. ; Zoidi, O. ; Tefas, Anastasios ; Pitas, Ioannis. / De-Identifying Facial Images Using Singular Value Decomposition. 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014): Proceedings of a meeting held 26-30 May 2014, Opatija, Croatia. Institute of Electrical and Electronics Engineers (IEEE), 2014. pp. 1240-1245

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title = "De-Identifying Facial Images Using Singular Value Decomposition",

abstract = "In this paper, a method is proposed that manipulates images in a manner that hinders face recognition by automatic recognition algorithms. The purpose of this method, is to partly degrade image quality, so that humans can identify the personor persons in a scene, while common classification algorithms fail to do so. The approach used to achieve this involves the use of singular value decomposition (SVD). From experiments it can be concluded that, the method reduces the percentage of correct classification rate by over 90% . In addition, the final image isnot degraded beyond recognition by humans.",

author = "P. Chriskos and O. Zoidi and Anastasios Tefas and Ioannis Pitas",

year = "2014",

month = sep,

doi = "10.1109/MIPRO.2014.6859757",

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booktitle = "2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014)",

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Chriskos, P, Zoidi, O, Tefas, A & Pitas, I 2014, De-Identifying Facial Images Using Singular Value Decomposition. in 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014): Proceedings of a meeting held 26-30 May 2014, Opatija, Croatia. Institute of Electrical and Electronics Engineers (IEEE), pp. 1240-1245, IEEE International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), oPATIJA/aBBAZIA, Croatia, 30/05/14. https://doi.org/10.1109/MIPRO.2014.6859757

De-Identifying Facial Images Using Singular Value Decomposition. / Chriskos, P.; Zoidi, O.; Tefas, Anastasios; Pitas, Ioannis.

2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014): Proceedings of a meeting held 26-30 May 2014, Opatija, Croatia. Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 1240-1245.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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T1 - De-Identifying Facial Images Using Singular Value Decomposition

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N2 - In this paper, a method is proposed that manipulates images in a manner that hinders face recognition by automatic recognition algorithms. The purpose of this method, is to partly degrade image quality, so that humans can identify the personor persons in a scene, while common classification algorithms fail to do so. The approach used to achieve this involves the use of singular value decomposition (SVD). From experiments it can be concluded that, the method reduces the percentage of correct classification rate by over 90% . In addition, the final image isnot degraded beyond recognition by humans.

AB - In this paper, a method is proposed that manipulates images in a manner that hinders face recognition by automatic recognition algorithms. The purpose of this method, is to partly degrade image quality, so that humans can identify the personor persons in a scene, while common classification algorithms fail to do so. The approach used to achieve this involves the use of singular value decomposition (SVD). From experiments it can be concluded that, the method reduces the percentage of correct classification rate by over 90% . In addition, the final image isnot degraded beyond recognition by humans.

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DO - 10.1109/MIPRO.2014.6859757

M3 - Conference Contribution (Conference Proceeding)

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EP - 1245

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PB - Institute of Electrical and Electronics Engineers (IEEE)

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ER -

Chriskos P, Zoidi O, Tefas A, Pitas I. De-Identifying Facial Images Using Singular Value Decomposition. In 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014): Proceedings of a meeting held 26-30 May 2014, Opatija, Croatia. Institute of Electrical and Electronics Engineers (IEEE). 2014. p. 1240-1245 https://doi.org/10.1109/MIPRO.2014.6859757

De-Identifying Facial Images Using Singular Value Decomposition

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