Relevant features for gender classification in NIR periocular images-Reference-Cited by-同舟云学术

Relevant features for gender classification in NIR periocular images

Published:2019-05-23 Issue:5 Volume:8 Page:340-350
ISSN:2047-4938
Container-title:IET Biometrics
language:en
Short-container-title:IET biom.

Author:

Viedma Ignacio¹,Tapia Juan²,Iturriaga Andres³,Busch Christoph⁴

Affiliation:

1. Engineering Science DepartmentUniversidad Andres BelloAv. Antonio Varas 880SantiagoChile

2. Universidad Tecnologica de ChileAvenida del Condor 720SantiagoChile

3. Faculty of MedicineUniversidad de Chile, Program of Biostatistics, School of Public HealthAv. Independencia 939SantiagoChile

4. da/sec – Biometrics and Internet Security Research GroupHochschule DarmstadtGermany

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-bmt.2018.5233

Reference45 articles.

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2. A survey on periocular biometrics research: an insight on eye biometrics;Alonso‐Fernandez F.;Pattern Recognit. Lett.,2016

3. Abdel Alim O. Sharkas M.: ‘Texture classification of the human iris using artificial neural networks’.11th Mediterranean Electrotechnical Conf. 2002. MELECON 2002 2002 pp.580–583

4. Popescu‐Bodorin N. Balas V.E. Motoc I.M.: ‘Iris codes classification using discriminant and witness directions’.5th Int. Symp. on Computational Intelligence and Intelligent Informatics (ISCIII) 2011 pp.143–148

5. Qiu X. Sun Z. Tan T.: ‘Global texture analysis of iris images for ethnic classification’.Int. Conf. on Advances in Biometrics ICB 2006 Hong Kong China 5–7 January2006 pp.411–418

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