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Exploring gender prediction from iris biometrics

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2015

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Gesellschaft für Informatik e.V.

Zusammenfassung

Prediction of gender characteristics from iris images has been investigated and some successful results have been reported in the literature, but without considering performance for different iris features and classifiers. This paper investigates for the first time an approach to gender prediction from iris images using different types of features (including a small number of very simple geometric features, texture features and a combination of geometric and texture features) and a more versatile and intelligent classifier structure. Our proposed approaches can achieve gender prediction accuracies of up to 90\% in the BioSecure Database.

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Fairhurst, Michael; Erbilek, Meryem; Da Costa-Abreu, Márjory (2015): Exploring gender prediction from iris biometrics. BIOSIG 2015. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-639-8. pp. 223-230. Darmstadt. 9.-11. September 2015

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