Local Orientation Binary Pattern with Use for Palmprint Recognition

  • Lunke FeiEmail author
  • Yong Xu
  • Shaohua Teng
  • Wei Zhang
  • Wenliang Tang
  • Xiaozhao Fang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10568)


In this paper, we extensively exploit the discriminative orientation features of palmprint, including the principal orientation and corresponding orientation confidence, and further propose a local orientation binary pattern (LOBP) for palmprint recognition. Different from the existing binary based representation methods, the LOBP method first captures the principal orientation consistency by comparing the center point with the neighbor sets, and then captures the confidence variations by thresholding the center confidence with neighborhoods so as to obtain orientation binary pattern (OBP) and confidence binary pattern (CBP), respectively. Furthermore, the block-wise statistics of OBP and CBP are concentrated to generate a novel descriptor, namely LOBP, of palmprint. Experiment results on different types of palmprint databases demonstrate the effectiveness of the proposed method.


Biometric Palmprint recognition Orientation binary pattern Confidence binary pattern 



This paper is partially supported by Guangdong Province high-level personnel of special support program (No. 2016TX03X164), and Shenzhen Fundamental Research fund (JCYJ20160331185006518).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Lunke Fei
    • 1
    Email author
  • Yong Xu
    • 2
  • Shaohua Teng
    • 1
  • Wei Zhang
    • 1
  • Wenliang Tang
    • 3
  • Xiaozhao Fang
    • 1
  1. 1.School of Computer Science and TechnologyGuangdong University of TechnologyGuangzhouChina
  2. 2.Shenzhen Graduate SchoolHarbin Institute of TechnologyShenzhenChina
  3. 3.School of SoftwareEast China Jiaotong UniversityNanchangChina

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