Generation of new points for training set and feature-level fusion in multimodal biometric identification

Karmakar, Dhiman; Murthy, C. A.

doi:10.1007/s00138-013-0532-y

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…Feature level fusion creates a composite feature vector by extracting and combining relevant and discriminant features from the original images. Feature level fusion faces challenges such as incompatibility of biometric vectors, dimensionality problems and difficulty of designing a matching algorithm for feature level matching [1]. Matching score level fusion combines the matching scores of each subsystem of the multibiometric system using techniques such as the weighted sum rule, weighted product, linear discriminant, decision tree, and the Bayesian rule.…”

Section: Figure 1 Taxonomy Of Biometricsmentioning

confidence: 99%

State of the Art in Biometric Key Binding and Key Generation Schemes

Jegede

Udzir

Abdullah

et al. 2022

Int. j. commun. netw. inf. secur.

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Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems.

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Section: Figure 1 Taxonomy Of Biometricsmentioning

confidence: 99%

State of the Art in Biometric Key Binding and Key Generation Schemes

Jegede

Udzir

Abdullah

et al. 2022

Int. j. commun. netw. inf. secur.

View full text Add to dashboard Cite

show abstract

“…They compared the recognition accuracy against match score level fusion. In recent research [34], face and iris were fused at the feature level using a new method based on minimum spanning tree. The comparison of their proposed method with traditional feature extractions like PCA, 2DPCA, and KPCA was an indicator of a better recognition result.…”

Section: Feature Level Fusionmentioning

confidence: 99%

Confidence Based Rank Level Fusion for Multimodal Biometric Systems

Talebi

Gavrilova

2015

Computer Analysis of Images and Patterns

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In recent years, the inevitable need for reliable biometric identity management systems in applications such as border crossing, welfare distribution, and accessing critical facilities has drawn researchers' attention to the area of biometric. The intrinsic limitations of unimodal biometric systems such as non-universality, sensitivity to noisy sensor data, inter and intra class variations and spoof attacks have resulted in significant attention toward multimodal biometric systems. An important aspect of a multimodal biometric system is the fusion of information from multiple biometric sources. This thesis focuses on using the notion of Resemblance Probability Distributions to calculate confidence measures for different biometric matchers and use these confidence measures in the fusion module to improve the identification rate of the system. This thesis approaches the problem of low inter class variation and low quality data by proposing Rank List Reinforcement and Confidence-based Ranked List Selection methods.

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Feature-level fusion of mental task’s brain signal for an efficient identification system

Kumari

Vaish

2015

Neural Comput & Applic

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Generation of new points for training set and feature-level fusion in multimodal biometric identification

Cited by 6 publications

References 27 publications

State of the Art in Biometric Key Binding and Key Generation Schemes

State of the Art in Biometric Key Binding and Key Generation Schemes

Confidence Based Rank Level Fusion for Multimodal Biometric Systems

Feature-level fusion of mental task’s brain signal for an efficient identification system

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