DMCA
Minutiae Extraction and Pruning Based Fingerprint Identification with Pattern Classification by Radial Basis Function
BibTeX
@MISC{Negi_minutiaeextraction,
author = {Nisha Negi and Sunil Semwal},
title = {Minutiae Extraction and Pruning Based Fingerprint Identification with Pattern Classification by Radial Basis Function},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Minutiae feature extraction is one of the most popular techniques used for fingerprint identification with great degree of success. This paper focuses on the enhancement in the performance of an Automatic Fingerprint Identification System in terms of FMR (false matching ratio) and FNMR (false non matching ratio). To achieve good results and make the system effective it is important to extract the minutiae features accurately. An algorithm is developed for minutiae extraction from fingerprints with varying quality, preprocessing in the form of filtering, binarization and thinning is first applied on fingerprint images before they are evaluated. Improved fingerprint pattern is generated by developing a feature pruning algorithm and then classification is done by radial basis function network. This developed algorithm is capable of finding the correspondences between input pruned fingerprint pattern and the stored template pattern without resorting to exhaustive search. The result has been analyzed on the basis that whether the system accepting an intruder or rejecting an authentic person.
Keyphrases
minutia extraction fingerprint identification radial basis function pattern classification fingerprint pattern stored template pattern popular technique exhaustive search automatic fingerprint identification system false non minutia feature extraction great degree radial basis function network good result authentic person developed algorithm fingerprint image
