A boosted cascade of directional local binary patterns for multispectral palmprint recognition

Linlin Shen, Bojie Liu, Jinwen He

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In this paper, a recently developed local feature descriptor, namely directional local binary patterns (DLBP), was first proposed for palmprint recognition. Compared with local binary patterns (LBP) and directional binary code (DBC), DLBP contains more information on both edge and texture. A cascade structure using AdaBoost algorithm is then used to reduce the feature dimension of DLBP and computational costs of classification. The proposed approach was applied to fuse multispectral palmprint images captured under red, green, blue and near-infrared (NIR) lighting sources for personal identification. Experimental results suggest that the proposed algorithm performs much better than DBC, LBP and PalmCode in identifying palmprint images captured using different illuminations. When fusing the multispectral images, the proposed approach has also been shown to achieve higher accuracy than other methods in literature such as QPCA (Quaternion PCA) and QDWT (Quaternion Discrete Wavelet Transform).

Original languageEnglish
Title of host publicationBiometric Recognition - 8th Chinese Conference, CCBR 2013, Proceedings
Pages233-240
Number of pages8
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2012 International Conference on Service-Oriented Computing, ICSOC 2012 - Jinan, China
Duration: 16 Nov 201317 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8232 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2012 International Conference on Service-Oriented Computing, ICSOC 2012
Country/TerritoryChina
CityJinan
Period16/11/1317/11/13

Keywords

  • Directional local binary patterns
  • Fusion
  • Palmprint recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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