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96269

Feature Level Fusion of Iris and Voice.

Article

Last updated: 04 Jan 2025

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Subjects

-

Tags

Electronics and Communications Engineering

Abstract

Biometric systems are vastly used by various organizations for different security applications. The main use of such systems is in authentication and identification applications which including computer network login, passport control, corpse identification, electronic data security, terrorist identification, Internet access. Unimodal biometric systems suffer from a lot of problems like high error rate, low performance and imposters' attack so the demand of Multimodal biometric systems takes place. Multimodal biometric systems have several advantages over unimodal biometric systems such as non-universality, larger population coverage, lower error rates, higher performance and higher genuine acceptance rates. In this paper, a study of multimodal fusion of voice and Iris at feature level is presented. The features are extracted from the voice signals using Power-Normalized Cepstral Coefficients (PNCC) and from the preprocessed iris images using Single Value Decomposition (SVD). The experiment have been done using samples collected from faculty of Engineering , Mansoura university for voice and CASIA iris database  for iris which gave accuracy of 98.4% after fusion. This result is acceptable and gives high accuracy than using voice and iris individually.

DOI

10.21608/bfemu.2020.96269

Keywords

Multimodal, Feature level fusion, voice recognition, Iris recognition

Authors

First Name

Sally

Last Name

Sameh

MiddleName

Mohamed

Affiliation

Electronics and Communications Engineering Department , Faculty of Engineering, Mansoura University, Mansoura, Egypt

Email

sally__sameh@hotmail.com

City

-

Orcid

-

First Name

Hossam El-Din

Last Name

Moustafa

MiddleName

Salah

Affiliation

Electronics and Communications Engineering Department , Faculty of Engineering, Mansoura University, Mansoura, Egypt

Email

hossam_moustafa@hotmail.com

City

-

Orcid

-

First Name

Fayez

Last Name

Zaki

MiddleName

Wanis

Affiliation

Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt

Email

fwzaki@yahoo.com

City

-

Orcid

-

Volume

40

Article Issue

5

Related Issue

14486

Issue Date

2015-12-01

Receive Date

2015-11-20

Publish Date

2021-12-01

Page Start

55

Page End

63

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 40_Issue 5_Pages 55-63.pdf

PDF . 869.1kB

Link

https://bfemu.journals.ekb.eg/article_96269.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=96269

Order

6

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

Feature Level Fusion of Iris and Voice.

Details

Type

Article

Created At

22 Jan 2023