A Modified Cancelable Biometrics Scheme Using Random Projection

Randa F. Soliman (), Mohamed Amin and Fathi E. Abd El-Samie
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Randa F. Soliman: Menoufia University
Mohamed Amin: Menoufia University
Fathi E. Abd El-Samie: Menoufia University

Annals of Data Science, 2019, vol. 6, issue 2, No 3, 223-236

Abstract: Abstract This paper presents a random projection scheme for cancelable iris recognition. Instead of using original iris features, masked versions of the features are generated through the random projection in order to increase the security of the iris recognition system. The proposed framework for iris recognition includes iris localization, sector selection of the iris to avoid eyelids and eyelashes effects, normalization, segmentation of normalized iris region into halves, selection of the upper half for further reduction of eyelids and eyelashes effects, feature extraction with Gabor filter, and finally random projection. This framework guarantees exclusion of eyelids and eyelashes effects, and masking of the original Gabor features to increase the level of security. Matching is performed with a Hamming Distance (HD) metric. The proposed framework achieves promising recognition rates of 99.67% and a leading Equal Error Rate (EER) of 0.58%.

Keywords: Iris recognition; Cancelable biometrics; Random projection (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s40745-018-0172-1

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