Research Article
Personal Identification from Lip-Print Features using a Statistical Model
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 55 - Issue 13 |
| Published: October 2012 |
| Authors: Saptarshi Bhattacharjee, S Arunkumar, Samir Kumar Bandyopadhyay |
10.5120/8817-2801
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Saptarshi Bhattacharjee, S Arunkumar, Samir Kumar Bandyopadhyay . Personal Identification from Lip-Print Features using a Statistical Model. International Journal of Computer Applications. 55, 13 (October 2012), 30-34. DOI=10.5120/8817-2801
@article{ 10.5120/8817-2801,
author = { Saptarshi Bhattacharjee,S Arunkumar,Samir Kumar Bandyopadhyay },
title = { Personal Identification from Lip-Print Features using a Statistical Model },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 55 },
number = { 13 },
pages = { 30-34 },
doi = { 10.5120/8817-2801 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Saptarshi Bhattacharjee
%A S Arunkumar
%A Samir Kumar Bandyopadhyay
%T Personal Identification from Lip-Print Features using a Statistical Model%T
%J International Journal of Computer Applications
%V 55
%N 13
%P 30-34
%R 10.5120/8817-2801
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper presents a novel approach towards identification of human beings from the statistical analysis of their lip prints. Lip features are extracted by studying the spatial orientations of the grooves present in lip prints of individuals using standard edge detection techniques. Horizontal, vertical and diagonal groove features are analysed using connected-component analysis to generate the region-specific edge datasets. Comparison between test and reference sample datasets against a threshold value to define a match yield satisfactory results. FAR, FRR and ROC metrics have been used to gauge the performance of the algorithm for real-world deployment in unimodal and multimodal biometric verification systems.
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