Paper Info
Title
A Fuzzy-Based Two-Stage Biometric Sample Quality Evaluation System
Abstract
Performance of biometric systems is highly dependent on the quality of the input samples captured by the sensing device. Although measures are taken for capturing high quality images, but the authentication system mandates the analysis of captured images for selection of precise data. The benefit of such an analysis are two-fold; it helps to identify the best sample, and is useful for improving the sensor design, user interface for sample collection and providing data interchange standards. In this work, we propose to analyse the quality of the sample data by using a two-stage fuzzy quality evaluation system. The proposed work has been demonstrated on the iris images using CASIA - 3.0 Interval, CASIA - 4.0 Interval and IIT Delhi iris database. We evaluate the quality of the images by classifying them into classes. The experimental results verify the efficacy of the proposed method.
Year
DOI
Venue
2019
10.1109/icassp.2019.8682844
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Biometric Quality, Fuzzy System, Local Quality Feature, Global Quality Feature
Iris recognition,Evaluation system,Pattern recognition,Authentication system,Computer science,Fuzzy logic,Feature extraction,Image segmentation,Artificial intelligence,Biometrics,User interface
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Tauheed Ahmed102.03
Monalisa Sarma2105.24
Debasis Samanta322737.98