A dynamically weighted multi-modal biometric security system

Title: A dynamically weighted multi-modal biometric security system
Creator: Brown, Dane L, Bradshaw, Karen L
Subject: To be catalogued
Date: 2016
Type: text
Type: book
Identifier: http://hdl.handle.net/10962/476629
Identifier: vital:77945
Identifier: ISBN 9780620724180
Description: The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than the match score-level. However, leveraging this potential requires a new approach. This work demonstrates a novel dynamic weighting algorithm for improved image-based biometric feature-fusion. A comparison is performed on uni-modal, bi-modal, tri-modal and proposed dynamic approaches. The proposed dynamic approach yields a high genuine acceptance rate of 99.25% genuine acceptance rate at a false acceptance rate of 1% on challenging datasets and big impostor datasets.
Format: 5 pages, pdf
Publisher: SATNAC
Language: English
Relation: Brown, D. and Bradshaw, K. 2016. A dynamically weighted multi-modal biometric security system. Southern Africa Telecommunication Networks and Applications Conference (SATNAC), 4-7 September 2016, George, p. 254-258
Rights: Authors
Rights: Use of this resource is governed by the terms and conditions of the SATNAC Copyright (https://www.satnac.org.za/proceedings)

Collections

Brown, Dane Lesley (Associate Prof)

SDG 09. Industry, Innovation and Infrastructure

RU Department of Computer Science

Bradshaw, Karen Lee (Assoc Prof)

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