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Proceedings ArticleDOI

On-line fingerprint verification

Anil K. Jain, +1 more
- Vol. 3, pp 596-600
TLDR
An improved minutia extraction algorithm that is much faster and more accurate than an earlier algorithm has been implemented and an alignment-based elastic matching algorithms has been developed for minutian matching.
Abstract
We describe the design and implementation of an online fingerprint verification system which operates in two stages: (i) minutia extraction and (ii) minutia matching. An improved minutia extraction algorithm that is much faster and more accurate than our earlier algorithm has been implemented. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between input minutiae and the stored template without resorting to exhaustive search and has the ability to adaptively compensate for the nonlinear deformations and inexact pose transformations between finger prints. The system has been tested on two sets of finger print images captured with inkless scanners. The verification accuracy is found to be over 99% with a 15% reject rate. Typically, a complete fingerprint verification procedure takes, on an average, about 8 seconds on a SPARC 20 workstation. It meets the response time requirements of on-line verification with high accuracy.

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Citations
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Journal ArticleDOI

An identity-authentication system using fingerprints

TL;DR: The design and implementation of a prototype automatic identity-authentication system that uses fingerprints to authenticate the identity of an individual is described and an improved minutiae-extraction algorithm is developed that is faster and more accurate than the earlier algorithm.
Book

Guide to Biometrics

TL;DR: This complete, technical guide details the principles, methods, technologies, and core ideas used in biometric authentication systems and defines and explains how to measure the performance of both verification and identification systems.
Journal ArticleDOI

A multichannel approach to fingerprint classification

TL;DR: This work presents a fingerprint classification algorithm which is able to achieve an accuracy better than previously reported in the literature and is based on a two-stage classifier to make a classification.
Proceedings ArticleDOI

Fingerprint minutiae matching based on the local and global structures

TL;DR: The proposed minutiae matching scheme is suitable for an online processing due to its high processing speed and experimental results show the performance of the proposed technique.
Journal ArticleDOI

Fingerprint classification: a review

TL;DR: The main objective of this paper is to review the extensive research that has been done on fingerprint classification over the last four decades and discusses the fingerprint features that are useful for distinguishing fingerprint classes and reviews the methods of classification that have been applied to the problem.
References
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Book

Introduction to Algorithms

TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Journal ArticleDOI

A graduated assignment algorithm for graph matching

TL;DR: A graduated assignment algorithm for graph matching is presented which is fast and accurate even in the presence of high noise, and not restricted to any special class of graph, is applied to subgraph isomorphism, weighted graph matching, and attributed relational graph matching.
Journal ArticleDOI

Adaptive flow orientation-based feature extraction in fingerprint images

TL;DR: A reliable method for extracting structural features from fingerprint images is presented and a “goodness index” (GI) which compares the results of automatic extraction with manually extracted ground truth is evaluated.
Journal ArticleDOI

Fingerprint pattern classification

Masahiro Kawagoe, +1 more
- 28 Jun 1984 - 
TL;DR: In this method, fingerprint images are divided into 32 × 32 subregions to obtain direction pattern and feature parameters of the fingerprint are obtained by extracting major flow-line traces.
Book

Advances in Fingerprint Technology

TL;DR: In this article, a concise history of fingerprinting and a discussion of Live-Scan and Image Transmission networks are discussed, including physical, chemical, instrumental, and combination techniques, as well as new developments in fingerprint processing.
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