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GEFE: genetic & evolutionary feature extraction for periocular-based biometric recognition

Published: 15 April 2010 Publication History

Abstract

Personal identification using an individual's periocular skin texture (e.g. the texture of the skin around the eye) is a promising and exciting new biometric modality [11]. For the application presented in this paper, local binary patterns (LBPs) are used to extract 1416 features from the periocular regions of images within the Face Recognition Grand Challenge (FRGC) dataset. GEFE (Genetic & Evolutionary Feature Extraction) is then used to evolve optimized subsets of the original feature set. Our results show that not only do the evolved subsets consist of approximately 50% fewer features but they also have higher recognition rates.

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Cited By

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  • (2023)Automatic design of machine learning via evolutionary computationApplied Soft Computing10.1016/j.asoc.2023.110412143:COnline publication date: 1-Aug-2023
  • (2022)Effectiveness of Periocular Biometric Recognition Under Face Mask RestrictionsBreakthroughs in Digital Biometrics and Forensics10.1007/978-3-031-10706-1_11(241-255)Online publication date: 15-Oct-2022
  • (2012)Genetic and evolutionary methods for biometric feature reductionInternational Journal of Biometrics10.1504/IJBM.2012.0476424:3(220-245)Online publication date: 1-Jul-2012
  • Show More Cited By

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cover image ACM Conferences
ACMSE '10: Proceedings of the 48th annual ACM Southeast Conference
April 2010
488 pages
ISBN:9781450300643
DOI:10.1145/1900008
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 April 2010

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Author Tags

  1. genetic & evolutionary feature extraction
  2. periocular biometric recognition
  3. steady-state genetic algorithm

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  • Research-article

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ACM SE '10
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ACM SE '10: ACM Southeast Regional Conference
April 15 - 17, 2010
Mississippi, Oxford

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ACMSE '10 Paper Acceptance Rate 48 of 94 submissions, 51%;
Overall Acceptance Rate 502 of 1,023 submissions, 49%

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Cited By

View all
  • (2023)Automatic design of machine learning via evolutionary computationApplied Soft Computing10.1016/j.asoc.2023.110412143:COnline publication date: 1-Aug-2023
  • (2022)Effectiveness of Periocular Biometric Recognition Under Face Mask RestrictionsBreakthroughs in Digital Biometrics and Forensics10.1007/978-3-031-10706-1_11(241-255)Online publication date: 15-Oct-2022
  • (2012)Genetic and evolutionary methods for biometric feature reductionInternational Journal of Biometrics10.1504/IJBM.2012.0476424:3(220-245)Online publication date: 1-Jul-2012
  • (2012)Neurogenetic reconstruction of biometric templates: A new security threat?2012 Proceedings of IEEE Southeastcon10.1109/SECon.2012.6197072(1-8)Online publication date: Mar-2012
  • (2012)Dot pattern feature extraction, selection and matching using LBP, Genetic Algorithm and Euclidean distance2012 International Conference on Computing, Communication and Applications10.1109/ICCCA.2012.6179197(1-6)Online publication date: Feb-2012
  • (2011)GEFeS: Genetic & evolutionary feature selection for periocular biometric recognition2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)10.1109/CIBIM.2011.5949211(152-156)Online publication date: Apr-2011
  • (2011)Hybrid GAs for Eigen-based facial recognition2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)10.1109/CIBIM.2011.5949209(127-130)Online publication date: Apr-2011
  • (2011)SSGA & EDA based feature selection and weighting for face recognition2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949776(1375-1381)Online publication date: Jun-2011
  • (2010)Genetic-Based Type II Feature Extraction for Periocular Biometric RecognitionProceedings of the 2010 20th International Conference on Pattern Recognition10.1109/ICPR.2010.59(205-208)Online publication date: 23-Aug-2010
  • (2010)Genetic & Evolutionary Type II feature extraction for periocular-based biometric recognitionIEEE Congress on Evolutionary Computation10.1109/CEC.2010.5585948(1-4)Online publication date: Jul-2010

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