Phase-based periocular recognition with texture enhancement

Luis Rafael Marval-Pérez, Koichi Ito, Takafumi Aoki

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Access control and surveillance applications like walking-through security gates and immigration control points have a great demand for convenient and accurate biometric recognition in unconstrained scenarios with low user cooperation. The periocular region, which is a relatively new biometric trait, has been attracting much attention for recognition of an individual in such scenarios. This paper proposes a periocular recognition method that combines Phase-Based Correspondence Matching (PB-CM) with a texture enhancement technique. PB-CM has demonstrated high recognition performance in other biometric traits, e.g., face, palmprint and finger-knuckle-print. However, a major limitation for periocular region is that the performance of PB-CM degrades when the periocular skin has poor texture. We address this problem by applying texture enhancement and found out that variance normalization of texture significantly improves the performance of periocular recognition using PB-CM. Experimental evaluation using three public databases demonstrates the advantage of the proposed method compared with conventional methods.

Original languageEnglish
Pages (from-to)1351-1363
Number of pages13
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number10
Publication statusPublished - 2019


  • Biometrics
  • Periocular recognition
  • Phase features
  • Phase-based image matching
  • Phase-only correlation
  • Texture enhancement


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