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Asymmetry-Based Quality Assessment of Face Images

  • Guangpeng Zhang
  • Yunhong Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5876)

Abstract

Quality assessment plays an important role in biometrics field. Unlike the popularity of fingerprint and iris quality assessment, the evaluation of face quality is just started. To solve the incapability for performance prediction and remove the requirement for scale normalization of existing methods, three face quality measures are proposed in this paper. SIFT is utilized to extract scale insensitive feature points on face images, and three asymmetry-based quality measures are calculated by applying different constraints. Systematical experiments validate the efficacy of the proposed quality measures.

Keywords

Face Recognition Quality Measure Face Image Local Binary Pattern Scale Invariant Feature Transform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Guangpeng Zhang
    • 1
  • Yunhong Wang
    • 1
  1. 1.School of Computer Science and EngineeringBeihang University 

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