Multimodal Biometrics -- Sources, Architecture and Fusion Techniques: An Overview

Madhavi, G.; Raju, S. Viswanadha; Babu, A. Vinaya; Kumar, D. Srinivasa

doi:10.1109/isbast.2012.24

Cited by 25 publications

(5 citation statements)

References 9 publications

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“…Anu et. al have attempted to fuse Iris and Palmprint biometric data at the feature level [9]. They have captured a sparse representation of the Palmprint and Iris feature sets on the CASIA biometric database.…”

Section: Decision Levelmentioning

confidence: 99%

Bio-metric credential system: Multimodal cancelable anonymous identity management

Suresh

Radhika

2015

2015 IEEE International Advance Computing Conference (IACC)

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Digital transactions have permeated almost every sphere of activity in today's world. This increase in digital transactions has introduced additional and stringent requirements with regard to security and privacy. People reveal lots of personal information by compromising their private credentials during digital interactions. It is imperative that in addition to security of on-line transactions, user credentials must also be safeguarded. This has necessitated the requirement for a rigorous and foolproof credential system with provision for anonymous and revocable identity management system. Biometric system based identity management systems offer advantage over conventional knowledge and possession based systems. Considerable research has been undertaken in the past to identify newer and reliable biometrics for more efficient and secure identity management. Fusion of multiple biometrics to achieve better results is also an area of active research. However, making biometric credential systems revocable and anonymous without sacrificing efficiency and efficacy of detection, still remains a challenge. This survey paper makes an attempt to give an insight into the approaches that have been made in the direction of multimodal biometric fusion and into the various options that have been explored to make biometric authentication systems revocable and anonymous.

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Section: Decision Levelmentioning

confidence: 99%

Bio-metric credential system: Multimodal cancelable anonymous identity management

Suresh

Radhika

2015

2015 IEEE International Advance Computing Conference (IACC)

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“…In previous works several techniques for features combination were presented (Damer et al, 2013;Gudavalli et al, 2012;Scheidat et al, 2011;Shekhar et al, 2014). Here, we use a score value based on a linear combination of the acquired features.…”

Section: Classifiermentioning

confidence: 99%

Handwritten Text Verification on Mobile Devices

Júnior¹,

Vidal

Macchiavello

2015

Proceedings of the 10th International Conference on Computer Vision Theory and Applications

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In this work we propose an online verification system for both signature and isolated cursive words. The proposed system is designed to be used in a mobile device with limited computational capability. In the proposed scenario it is assumed that the user will use either his fingertip or a passive pen, therefore no azimuth or inclination information is available. Isolated words have certain desirable traits that can be more useful on a mobile device. Different isolated words can be used to verify the user in different applications, combining a knowledge-based security systems (i.e. passwords) with a behavioral biometric verification system. The proposed technique can achieve 4.39% of equal error rate for signatures and 6.5% for isolated words.

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“…Multimodal biometric approaches, characterization of their strengths, weaknesses, typical processing phases, systems architectures, operation modes, algorithms, and levels and methods of fusion can be found in works of Oloyede and Hancke [ 6 ], Ross and Jain work [ 4 , 7 ], and Gudavalli et al [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application

Szczuko

Harasimiuk

Czyżewski

2022

Sensors

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An evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application of DST, required modifications, base probability, and mass conversions. Next, the biometric verification process is described, and the engineered biometric banking system principles are provided. Finally, the validation results of three fusion approaches on synthetic and real data are presented and discussed, considering the desired outcome manifested by minimized false non-match rates for various assumed thresholds and biometric verification techniques.

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Multimodal Biometrics -- Sources, Architecture and Fusion Techniques: An Overview

Cited by 25 publications

References 9 publications

Bio-metric credential system: Multimodal cancelable anonymous identity management

Bio-metric credential system: Multimodal cancelable anonymous identity management

Handwritten Text Verification on Mobile Devices

Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application

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