Face liveness detection using defocus

Sooyeon Kim, Yuseok Ban, Sangyoun Lee

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


In order to develop security systems for identity authentication, face recognition (FR) technology has been applied. One of the main problems of applying FR technology is that the systems are especially vulnerable to attacks with spoofing faces (e.g., 2D pictures). To defend from these attacks and to enhance the reliability of FR systems, many anti-spoofing approaches have been recently developed. In this paper, we propose a method for face liveness detection using the effect of defocus. From two images sequentially taken at different focuses, three features, focus, power histogram and gradient location and orientation histogram (GLOH), are extracted. Afterwards, we detect forged faces through the feature-level fusion approach. For reliable performance verification, we develop two databases with a handheld digital camera and a webcam. The proposed method achieves a 3.29% half total error rate (HTER) at a given depth of field (DoF) and can be extended to camera-equipped devices, like smartphones.

Original languageEnglish
Pages (from-to)1537-1563
Number of pages27
JournalSensors (Switzerland)
Issue number1
Publication statusPublished - 2015 Jan 14

Bibliographical note

Publisher Copyright:
© 2015 by the authors; licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering


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