Eigen directional bit-planes for robust face recognition

Lei Lei, Seung Wook Kim, Won Jae Park, Dae Hwan Kim, Sung-Jea Ko

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

A visible image-based face recognition system can be seriously degraded in real-life environments by various factors including illumination changes, expression changes, occlusion, and disguise. In this paper, a novel feature descriptor for robust face recognition, Eigen Directional Bit-Plane (EDBP), is introduced to address these issues. It is observed that Local Binary Pattern (LBP) can be decomposed into 8 directional bit-planes (DBP), each of which represents certain directional information of the facial image. Principal Component Analysis (PCA) is then applied to the DBP space to obtain a more compact feature, the EDBP. For face recognition, the proposed EDBP is integrated into conventional state-of-the-art classification methods. Simulation results demonstrate that classifiers with EDBP outperform those with existing feature descriptors under illumination changes, expression changes, occlusion, and disguise.

Original languageEnglish
Article number7027346
Pages (from-to)702-709
Number of pages8
JournalIEEE Transactions on Consumer Electronics
Volume60
Issue number4
DOIs
Publication statusPublished - 2014 Nov 1

Keywords

  • Eigen Directional Bit-Plane (EDBP)
  • Face Recognition
  • Local Binary Pattern (LBP)
  • Principal Component Analysis (PCA)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Media Technology

Fingerprint Dive into the research topics of 'Eigen directional bit-planes for robust face recognition'. Together they form a unique fingerprint.

Cite this