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Cross-Spectral Periocular Recognition by Cascaded Spectral Image Transformation

Raja, Kiran and Damer, Naser and Ramachandra, Raghavendra and Boutros, Fadi and Busch, Christoph (2019):
Cross-Spectral Periocular Recognition by Cascaded Spectral Image Transformation.
pp. 1-7, 2019 IEEE International Conference on Imaging Systems and Techniques (IST), Abu Dhabi, United Arab Emirates, 09.-10. Dec., 2019, DOI: 10.1109/IST48021.2019.9010520,
[Conference or Workshop Item]

Abstract

Recent efforts in biometrics have focused on crossdomain face recognition where images from one domain are either transformed or synthesized. In this work, we focus on a similar problem for cross spectral periocular recognition where the images from Near Infra Red (NIR) domain are matched against Visible (VIS) spectrum images. Specifically, we propose to adapt a cascaded image transformation network that can produce NIR image given a VIS image. The proposed approach is first validated with regards to the quality of the image produced by employing various quality factors. Second the applicability is demonstrated with images generated by the proposed approach. We employ a publicly available cross-spectral periocular image data of 240 unique periocular instances captured in 8 different capture sessions. We experimentally validate that the proposed image transformation scheme can produce NIR like images and also can be used with any existing feature extraction scheme. To this extent, we demonstrate the biometric applicability by using both hand-crafted and deep neural network based features under verification setting. The obtained EER of 0.7% indicates the suitability of proposed approach for image transformation from the VIS to the NIR domain.

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Raja, Kiran and Damer, Naser and Ramachandra, Raghavendra and Boutros, Fadi and Busch, Christoph
Title: Cross-Spectral Periocular Recognition by Cascaded Spectral Image Transformation
Language: English
Abstract:

Recent efforts in biometrics have focused on crossdomain face recognition where images from one domain are either transformed or synthesized. In this work, we focus on a similar problem for cross spectral periocular recognition where the images from Near Infra Red (NIR) domain are matched against Visible (VIS) spectrum images. Specifically, we propose to adapt a cascaded image transformation network that can produce NIR image given a VIS image. The proposed approach is first validated with regards to the quality of the image produced by employing various quality factors. Second the applicability is demonstrated with images generated by the proposed approach. We employ a publicly available cross-spectral periocular image data of 240 unique periocular instances captured in 8 different capture sessions. We experimentally validate that the proposed image transformation scheme can produce NIR like images and also can be used with any existing feature extraction scheme. To this extent, we demonstrate the biometric applicability by using both hand-crafted and deep neural network based features under verification setting. The obtained EER of 0.7% indicates the suitability of proposed approach for image transformation from the VIS to the NIR domain.

Uncontrolled Keywords: Biometrics Multispectral images Face recognition
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Event Location: Abu Dhabi, United Arab Emirates
Event Dates: 09.-10. Dec., 2019
Date Deposited: 17 Apr 2020 10:25
DOI: 10.1109/IST48021.2019.9010520
Official URL: https://doi.org/10.1109/IST48021.2019.9010520
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