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Symmetry 2018, 10(4), 122; https://doi.org/10.3390/sym10040122

Cosmetic Detection Framework for Face and Iris Biometrics

Department of Computer and Software Engineering, Toros University, Mersin 33140, Turkey
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Received: 26 March 2018 / Revised: 15 April 2018 / Accepted: 16 April 2018 / Published: 19 April 2018
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Abstract

Cosmetics pose challenges to the recognition performance of face and iris biometric systems due to its ability to alter natural facial and iris patterns. Facial makeup and iris contact lens are considered to be commonly applied cosmetics for the face and iris in this study. The present work aims to present a novel solution for the detection of cosmetics in both face and iris biometrics by the fusion of texture, shape and color descriptors of images. The proposed cosmetic detection scheme combines the microtexton information from the local primitives of texture descriptors with the color spaces achieved from overlapped blocks in order to achieve better detection of spots, flat areas, edges, edge ends, curves, appearance and colors. The proposed cosmetic detection scheme was applied to the YMU YouTube makeup database (YMD) facial makeup database and IIIT-Delhi Contact Lens iris database. The results demonstrate that the proposed cosmetic detection scheme is significantly improved compared to the other schemes implemented in this study. View Full-Text
Keywords: biometrics; makeup detection; lens detection; face–iris modalities biometrics; makeup detection; lens detection; face–iris modalities
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Sharifi, O.; Eskandari, M. Cosmetic Detection Framework for Face and Iris Biometrics. Symmetry 2018, 10, 122.

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