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Soft Computing

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11.02.2019 | Focus

Quality-based pattern C² code score-level fusion in multimodal biometric authentication system using pattern net

verfasst von: S. Ilankumaran, C. Deisy, R. Pandian

Erschienen in: Soft Computing | Ausgabe 8/2019

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Abstract

Biometrics-based authentication is a most needed activity in a corporate and business world. Genuineness, accuracy and reliability are the most common characteristics of any authentication system. This requires any multimodal unique biometric traits combined with better fusion strategy. This paper have proposed C²-based fusion algorithm for combining the two complicated, unique, minute detailed finger vein and iris images for reduced feature vector extraction. A reduced feature vectors from this C² algorithm is given to the neural net known as pattern net for pattern matching. The combined strategy is applied for 250 data sets for verification and gives better performance in R² value, equal error rate, false acceptance rate, etc.

Vorheriger Artikel An adaptive neuro-fuzzy logic based jamming detection system in WSN

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Titel: Quality-based pattern C2 code score-level fusion in multimodal biometric authentication system using pattern net
verfasst von: S. Ilankumaran
C. Deisy
R. Pandian
Publikationsdatum: 11.02.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 8/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-03751-0

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