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Reseach Article

Adaptive Cascade Classifier based Multimodal Biometric Recognition and Identification System

by Ujwalla Gawande, Kamal Hajari
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 2
Year of Publication: 2013
Authors: Ujwalla Gawande, Kamal Hajari

Ujwalla Gawande, Kamal Hajari . Adaptive Cascade Classifier based Multimodal Biometric Recognition and Identification System. International Journal of Applied Information Systems. 6, 2 ( September 2013), 42-47. DOI=10.5120/ijais13-451019

@article{ 10.5120/ijais13-451019,
author = { Ujwalla Gawande, Kamal Hajari },
title = { Adaptive Cascade Classifier based Multimodal Biometric Recognition and Identification System },
journal = { International Journal of Applied Information Systems },
issue_date = { September 2013 },
volume = { 6 },
number = { 2 },
month = { September },
year = { 2013 },
issn = { 2249-0868 },
pages = { 42-47 },
numpages = {9},
url = { },
doi = { 10.5120/ijais13-451019 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2023-07-05T17:59:36.519593+05:30
%A Ujwalla Gawande
%A Kamal Hajari
%T Adaptive Cascade Classifier based Multimodal Biometric Recognition and Identification System
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 6
%N 2
%P 42-47
%D 2013
%I Foundation of Computer Science (FCS), NY, USA

Biometrics consists of techniques for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits such as Iris, fingerprint, Face and Palm geometry etc. To overcome the limitations of Unimodal biometric system, a multimodal biometric is proposed. Amongst the various fusion levels, feature level fusion is expected to offer better recognition. Feature level fusion fused the extracted feature obtained from biometric traits. The proposed system is based on feature level fusion and adaptive cascade classifier for precise and reliable multimodal recognition and identification. Verification of Genuine and imposter individual classification is done using Backpropagation neural network. The simulation results demonstrated that a multibiometric template provides better recognition performance compared to a unibiometric template and adaptive cascade classification system significantly outperforms single classifier.

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Index Terms

Computer Science
Information Sciences


Neural network Multimodal single algorithmic Multi algorithmic Train and Test parameters and Backpropagation neural network.