Age estimation-based soft biometrics considering optical blurring based on symmetrical sub-blocks for MLBP

Dat Tien Nguyen, So Ra Cho, Kang Ryoung Park

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Because of its many useful applications, human age estimation has been considered in many previous studies as a soft biometrics. However, most existing methods of age estimation require a clear and focused facial image as input in order to obtain a trustworthy estimation result; otherwise, the methods might produce increased estimation error when an image of poor quality is used as input. Image blurring is one of major factors that affect estimation accuracies because it can cause a face to appear younger (i.e., reduce the age feature in the face region). Therefore, we propose a new human age estimation method that is robust even with an image that has the optical blurring effect by using symmetrical focus mask and sub-blocks for multi-level local binary pattern (MLBP). Experiment results show that the proposed method can enhance age estimation accuracy compared with the conventional system, which does not consider the effects of blurring.

Original languageEnglish
Pages (from-to)1882-1913
Number of pages32
JournalSymmetry
Volume7
Issue number4
DOIs
StatePublished - 2015

Keywords

  • Focus mask
  • Human age estimation
  • Optical blurring effect
  • Soft biometrics
  • Symmetrical sub-blocks for MLBP

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