Auflistung nach Autor:in "Erbilek, Meryem"
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- KonferenzbeitragExploring gender prediction from iris biometrics(BIOSIG 2015, 2015) Fairhurst, Michael; Erbilek, Meryem; Da Costa-Abreu, MárjoryPrediction 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.
- KonferenzbeitragImproved age prediction from biometric data using multimodal configurations(BIOSIG 2014, 2014) Erbilek, Meryem; Fairhurst, Michael; Da Costa-Abreu, MárjoryThe prediction of individual characteristics from biometric data which falls short of full identity prediction is nevertheless a valuable capability in many practical applications. This paper considers age prediction in two biometric modalities (iris and handwritten signature) and explores how different feature types and classification strategies can be used to overcome possible constraints in different data capture scenarios. Importantly, the paper also explores for the first time the use of multimodal combination of these two modalities in an age prediction task.