Paper Info
Title
Fingerprint Recognition Using Minutia Score Matching
Abstract
The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person's life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae from the thinned image. The false matching ratio is better compared to the existing algorithm. Key-words:-Fingerprint Recognition, Binarization, Block Filter Method, Matching score and Minutia. I. Introduction Biometric systems operate on behavioral and physiological biometric data to identify a person. The behavioral biometric parameters are signature, gait, speech and keystroke, these parameters change with age and environment. However physiological characteristics such as face, fingerprint, palm print and iris remains unchanged through out the life time of a person. The biometric system operates as verification mode or identification mode depending on the requirement of an application. The verification mode validates a person's identity by comparing captured biometric data with ready made template. The identification mode recognizes a person's identity by performing matches against multiple fingerprint biometric templates. Fingerprints are widely used in daily life for more than 100 years due to its feasibility, distinctiveness, permanence, accuracy, reliability, and acceptability. Fingerprint is a pattern of ridges, furrows and minutiae, which are extracted using inked impression on a paper or sensors. A good quality fingerprint contains 25 to 80 minutiae depending on sensor resolution and finger placement on the sensor. The false minutiae are the false ridge breaks due to insufficient amount of ink and cross-connections due to over inking. It is difficult to extract reliably minutia from poor quality fingerprint impressions arising from very dry fingers and fingers mutilated by scars, scratches due to accidents, injuries. Minutia based fingerprint recognition consists of Thinning, Minutiae extraction, Minutiae matching and Computing matching score. Motivation: The motivation behind the work is growing need to identify a person for security. The fingerprint is one of the popular biometric methods used to authenticate human being. The proposed fingerprint verification FRMSM provides reliable and better performance than the existing technique. Contribution: In this paper we used Fingerprint Recognition using Minutia Score Matching method with the help of MATLAB codes. Minutiae are extracted from the thinned image for both template and input image. Finally both the images are subjected to matching process and matching score is computed. Organization: This paper is organized into the following sections. Section II is an overview of the related work, in section III describes Model for fingerprint recognition in detail. Section IV gives the algorithm. In section V performance analysis and results are discussed and finally in section VI give the conclusions.
Year
Venue
Keywords
2010
Computing Research Repository
fingerprint verification,fingerprint recognition
Field
DocType
Volume
Computer vision,Authentication,Palm print,Pattern recognition,Minutiae,Fingerprint recognition,Fingerprint Verification Competition,Computer science,Keystroke logging,Fingerprint,Artificial intelligence,Biometrics
Journal
abs/1001.4186
ISSN
Citations 
PageRank 
IJEST Volume 1 Issue 2 2009 35-42
8
0.53
References 
Authors
10
3
Name
Order
Citations
PageRank
J. Ravi180.53
K. B. Raja2349.60
K. R. Venugopal326748.80