An empirical study of palmprint recognition for mobile phones

Jin Su Kim; Gen Li; Byungjun Son; Jaihie Kim

doi:10.1109/TCE.2015.7298090

An empirical study of palmprint recognition for mobile phones

Jin Su Kim, Gen Li, Byungjun Son, Jaihie Kim

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

18 Citations (Scopus)

Abstract

Limited processing power, hand pose variations, complicated backgrounds and changing illumination are some of the inherent problems in mobile palmprint recognition. In this paper, a hand-shaped guide window is proposed for fast processing of image acquisition, valley point detection and verification to deal with such problems. Also, an improved version of the Competitive Code is proposed in order to cope with the variation in mobile images, and two practical verification scenarios are suggested to further improve the verification performance. A palmprint database was established using mobile phones for experiments, and an equal error rate (EER) of 2.88% was achieved by using the conventional 1-to-1 matching strategy. By applying the suggested practical scenarios, the verification accuracy was improved to achieve an EER of 0.97%.

Original language	English
Article number	7298090
Pages (from-to)	311-319
Number of pages	9
Journal	IEEE Transactions on Consumer Electronics
Volume	61
Issue number	3
DOIs	https://doi.org/10.1109/TCE.2015.7298090
Publication status	Published - 2015 Aug 1

Bibliographical note

Publisher Copyright:
© 1975-2011 IEEE.

All Science Journal Classification (ASJC) codes

Media Technology
Electrical and Electronic Engineering

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10.1109/TCE.2015.7298090

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AB - Limited processing power, hand pose variations, complicated backgrounds and changing illumination are some of the inherent problems in mobile palmprint recognition. In this paper, a hand-shaped guide window is proposed for fast processing of image acquisition, valley point detection and verification to deal with such problems. Also, an improved version of the Competitive Code is proposed in order to cope with the variation in mobile images, and two practical verification scenarios are suggested to further improve the verification performance. A palmprint database was established using mobile phones for experiments, and an equal error rate (EER) of 2.88% was achieved by using the conventional 1-to-1 matching strategy. By applying the suggested practical scenarios, the verification accuracy was improved to achieve an EER of 0.97%.

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An empirical study of palmprint recognition for mobile phones

Abstract

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