Combining sclera and periocular features for multi-modal identity verification

Kangrok Oh, Beom Seok Oh, Kar Ann Toh, Wei Yun Yau, How Lung Eng

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)


In this paper, we propose to combine sclera and periocular features for identity verification. The proposal is particularly useful in applications related to face recognition when the face is partially occluded with only periocular region revealed. Due to its relatively new exposition in the literature of biometrics, particular attention will be paid to sclera feature extraction in this work. For periocular feature extraction, structured random projections were adopted to extract compressed vertical and horizontal components of image features. The binary sclera features are eventually fused with the periocular features at a score level. Extensive experiments have been performed on UBIRIS v1 session1 and session2 databases to assess the verification performance before and after fusion. Around 5% of equal error rate performance was observed to be enhanced by fusing sclera with periocular features comparing with that before fusion.

Original languageEnglish
Pages (from-to)185-198
Number of pages14
Publication statusPublished - 2014 Mar 27

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government ( NRF-2011-013-D00099 ).

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence


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