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Palm Print and Palm Vein Joint Recognition System Based on Video

WANG Hao1 KANG Wenxiong1 CHEN Xiaopeng1

(1.School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China 510641)

【Abstract】A novel palm print and palm vein joint recognition system based on video is built. First of all, a novel registration and identification approach is proposed. Instead of getting static image by traditional collection method, we obtain the palm motion video though the proposed system. The approach allows the users to simply sweep their palms over the acquisition platform without stop, which effectively enhances the affinity of authentication. A new strategy of fusing rotating videos with sweeping videos to generate the register feature set is proposed, which ensures the abundance and integrality of the register feature and enhances the robustness of the system to various palm postures in authentication. A cascade fusion strategy is presented to improve the recognition speed of the registered users. We construct a palm print and palm vein database containing 1 200 videos with motion blur from 100 palms and carry out a series of simulations. The results show that the proposed system can achieve a low equal error rate of 1.51% within the expected time consumption of 915 ms, which demonstrates the effectiveness and practicality of the new system.

【Keywords】 machine vision; biometrics authentication; palm print recognition; palm vein recognition; cascade fusion;

【DOI】

【Funds】 National Natural Science Foundation of China (61573151) Natural Science Foundation of Guangdong Province (2016A030313468) Science and Technology Program of Guangdong Province (2017A010101026) Science and Technology Program of Guangzhou City (201510010088)

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This Article

ISSN:0253-2239

CN:31-1252/O4

Vol 38, No. 02, Pages 248-256

February 2018

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Article Outline

Abstract

  • 1 Introduction
  • 2 Introduction to the palm print and palm vein recognition system
  • 3 Video frame screening
  • 4 Extraction and matching of palm texture template
  • 5 Extraction and matching of local invariant features of palm print
  • 6 Cascade fusion in decision-making level
  • 7 Simulation results analysis
  • 8 Conclusion
  • References