Vein point cloud registration algorithm for multi-pose hand vein authentication

Yong Qi, Ya Zhou, Chang Zhou, Xinran Hu, Xiaoming Hu

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

5 Citations (Scopus)

Abstract

Traditional vein recognition technology is usually based on the 2D infrared images of hand vein. However, the hand vein patterns extracted from 2D images are seriously distorted with hand posture changes. A point cloud matching vein recognition system based on Kernel Correlation(KC) algorithm is designed, which provides a new perspective to hand vein recognition but also suffers from posture change because KC value is sensitive to coordinate shift. In this paper, a vein point cloud registration algorithm is proposed to improve the vein authentication under multi-pose. Experiments show that the point cloud registration algorithm can effectively improve the recognition rate. After the point cloud registration, when the hand posture changes limited to the range ± 20 degrees, the system can keep more than 90% recognition rate, the corresponding error rate is only 4%.

Original languageEnglish
Title of host publicationISBA 2016 - IEEE International Conference on Identity, Security and Behavior Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467397278
DOIs
Publication statusPublished - 23 May 2016
Event2nd IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2016 - Sendai, Japan
Duration: 29 Feb 20162 Mar 2016

Publication series

NameISBA 2016 - IEEE International Conference on Identity, Security and Behavior Analysis

Conference

Conference2nd IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2016
Country/TerritoryJapan
CitySendai
Period29/02/162/03/16

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