- Title
- Deep face-iris recognition using robust image segmentation and hyperparameter tuning
- Creator
- Brown, Dane L
- Subject
- To be catalogued
- Date
- 2022
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/465145
- Identifier
- vital:76577
- Identifier
- xlink:href="https://link.springer.com/chapter/10.1007/978-981-16-3728-5_19"
- Description
- Biometrics are increasingly being used for tasks that involve sensitive or financial data. Hitherto, security on devices such as smartphones has not been a priority. Furthermore, users tend to ignore the security features in favour of more rapid access to the device. A bimodal system is proposed that enhances security by utilizing face and iris biometrics from a single image. The motivation behind this is the ability to acquire both biometrics simultaneously in one shot. The system’s biometric components: face, iris(es) and their fusion are evaluated. They are also compared to related studies. The best results were yielded by a proposed lightweight Convolutional Neural Network architecture, outperforming tuned VGG-16, Xception, SVM and the related works. The system shows advancements to ‘at-a-distance’ biometric recognition for limited and high computational capacity computing devices. All deep learning algorithms are provided with augmented data, included in the tuning process, enabling additional accuracy gains. Highlights include near-perfect fivefold cross-validation accuracy on the IITD-Iris dataset when performing identification. Verification tests were carried out on the challenging CASIA-Iris-Distance dataset and performed well on few training samples. The proposed system is practical for small or large amounts of training data and shows great promise for at-a-distance recognition and biometric fusion.
- Format
- computer, online resource, application/pdf, 1 online resource (16 pages), pdf
- Publisher
- SpringerLink
- Language
- English
- Relation
- Computer Networks and Inventive Communication Technologies: Proceedings of Fourth ICCNCT 2021, Brown, D., 2022. Deep face-iris recognition using robust image segmentation and hyperparameter tuning. In Computer Networks and Inventive Communication Technologies: Proceedings of Fourth ICCNCT 2021 (pp. 259-275). Springer Singapore, Computer Networks and Inventive Communication Technologies: Proceedings of Fourth ICCNCT 2021 p. 259 2022 2367-4520
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the SpringerLink Terms of Use Statement ( https://link.springer.com/termsandconditions)
- Rights
- Closed Access
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- Visitors: 47
- Downloads: 2
Collections
Brown, Dane A (Dr)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | Deep face-iris recognition using robust image segmentation and hyperparameter tuning.pdf | 701 KB | Adobe Acrobat PDF | View Details |