- Title
- Feature-fusion guidelines for image-based multi-modal biometric fusion
- Creator
- Brown, Dane L, Bradshaw, Karen L
- Subject
- To be catalogued
- Date
- 2017
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/465689
- Identifier
- vital:76632
- Identifier
- xlink:href="https://hdl.handle.net/10520/EJC-90afb1388"
- Description
- The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our 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 vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.
- Format
- computer, online resource, application/pdf, 1 online resource (29 pages), pdf
- Publisher
- Sabinet
- Language
- English
- Relation
- South African Computer Journal, 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, 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 Sabinet Terms and Conditions Statement (https://www.sabinet.co.za/terms-conditions)
- Rights
- Closed Access
- Hits: 42
- Visitors: 44
- Downloads: 2
Collections
Brown, Dane A (Dr)
RU Department of Computer Science
Bradshaw, Karen Lee (Assoc Prof)
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | Feature-fusion guidelines for image-based multi-modal biometric fusion.pdf | 665 KB | Adobe Acrobat PDF | View Details |