- Title
- Feature-fusion guidelines for image-based multi-modal biometric fusion
- Creator
- Brown, Dane L
- Creator
- Bradshaw, Karen L
- Subject
- To be catalogued
- Date Issued
- 2017
- Date
- 2017
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/460063
- Identifier
- vital:75889
- Identifier
- xlink:href="https://doi.org/10.18489/sacj.v29i1.436"
- Description
- The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a newapproach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprintand palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed inour recent work, are extended by adding a new face segmentation method and the support vector machine classifier.The new face segmentation method improves the face identification equal error rate (EER) by 10%. The support vectormachine classifier combined with the new feature selection approach, proposed in our recent work, outperforms otherclassifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknessesas observed in the applied feature processing modules during preliminary experiments. The guidelines are used toimplement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducingthe EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face,MCYT Fingerprint and CASIA Palmprint.
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (30 pages)
- Format
- Publisher
- South African Computer Society
- Language
- English
- Relation
- South African Computer Journal
- Relation
- Brown, D. and Bradshaw, K., 2017. Feature-fusion guidelines for image-based multi-modal biometric fusion. South African Computer Journal, 29(1), pp.92-121
- Relation
- South African Computer Journal volume 29 number 1 p. 92 2017 2313-7835
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the Creative Commons CC BY-NC-ND 4.0 License (Attribution-NonCommercial-NoDerivatives 4.0 International) https://creativecommons.org/licenses/by-nc-nd/4.0/
- Rights
- Open Access
- Hits: 78
- Visitors: 76
- Downloads: 2
Collections
Brown, Dane A (Associate Prof)
RU Department of Computer Science
Bradshaw, Karen Lee (Assoc Prof)
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Feature-fusion guidelines for image-based multi-modal biometric fusion.pdf | 1 MB | Adobe Acrobat PDF | View Details Download |