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HYBRID ANN AND FIREWORKS ALGORITHM FOR REAL-TIME SOFTWARE RELIABILITY PREDICTION

Ivy Botchway Felix Larbi Aryeh Boniface Kayode Alese
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Statistical Descriptors for Fingerprint Matching

by Ravinder Kumar, Pravin Chandra, M. Hanmandlu
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 16
Year of Publication: 2012
Authors: Ravinder Kumar, Pravin Chandra, M. Hanmandlu
10.5120/9633-4361

Ravinder Kumar, Pravin Chandra, M. Hanmandlu . Statistical Descriptors for Fingerprint Matching. International Journal of Computer Applications. 59, 16 ( December 2012), 24-27. DOI=10.5120/9633-4361

@article{ 10.5120/9633-4361,
author = { Ravinder Kumar, Pravin Chandra, M. Hanmandlu },
title = { Statistical Descriptors for Fingerprint Matching },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 16 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 24-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number16/9633-4361/ },
doi = { 10.5120/9633-4361 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:04:23.304487+05:30
%A Ravinder Kumar
%A Pravin Chandra
%A M. Hanmandlu
%T Statistical Descriptors for Fingerprint Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 16
%P 24-27
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a novel algorithm for fingerprint matching using statistical descriptors. This fingerprint-matching algorithm overcomes the problems faced during matching of low quality fingerprint images. The steps of the algorithm include extraction of core point using Poincare index method, extraction of Region of Interest (ROI) around core point, and similarity evaluation of statistical descriptors using k-NN classifier. Statistical descriptors are computed from 16 Gray Level Co-occurrence Matrices (GLCM) from Extracted ROI. The proposed algorithm is evaluated on the FVC2002 DB2 database. The experimental results show the effectiveness of proposed algorithm. Computational efficiency is improved by considering the ROI of size 101 ? 101 around the core point.

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Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint Identification Statistical Descriptor Genuine Acceptance Rate False Acceptance Rate Feature Extraction

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