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A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue

by Gaganpreet Kaur, Dheerendra Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 7
Year of Publication: 2015
Authors: Gaganpreet Kaur, Dheerendra Singh
10.5120/21082-3764

Gaganpreet Kaur, Dheerendra Singh . A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue. International Journal of Computer Applications. 119, 7 ( June 2015), 30-39. DOI=10.5120/21082-3764

@article{ 10.5120/21082-3764,
author = { Gaganpreet Kaur, Dheerendra Singh },
title = { A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 7 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number7/21082-3764/ },
doi = { 10.5120/21082-3764 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:03:27.226164+05:30
%A Gaganpreet Kaur
%A Dheerendra Singh
%T A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 7
%P 30-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There is urgent need to make behavioural biometric systems more reliable, robust and accurate. This paper presents feature level fusion of offline signature and speech and tongue biometrics. The fusion of speech and signature with tongue made the system more efficient. MFCC is used for feature extraction in speech and in signature DCT is used which is widely used for image and texture feature extraction. While the features of tongue are extracted using SIFT algorithm. Hybrid weighted average using Apirori two item set is applied for the fusion of extracted features of all the modalities. SVC2004 signature database are used for experimental results. Tongue database was collected by capturing pictures using digital camera while for speech CMU_ARCTIC database which is available at Language Technologies Institute at Carnegie Mellon University is used in the work. Features for both noisy and non-noisy samples have been collected separately. Gaussian noise was added to the system to check the performance in noisy environment. The proposed system also works efficiently on filtered noisy modalities with accuracy of 80%. The accuracy of the noiseless system is 88. 75% with 0. 06 % of FAR and with 0. 05% of FRR and the noisy system have FAR 0. 05% and FRR 0. 15%. The ROC curves are calculated.

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Index Terms

Computer Science
Information Sciences

Keywords

Biometric Multimodal Biometric SIFT Mel Frequency Cepstral Coefficient Discrete Cosine Transformation Apriori Algorithm Weighted Averaging Motion Blur filter False Acceptance Rate False Rejection Rate ROC.

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