Multi-unit iris recognition system by image check algorithm

Jain Jang, Kang Ryoung Park, Jinho Son, Yillbyung Lee

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

14 Scopus citations

Abstract

In this paper, we propose the iris recognition system, which can select the good quality data between left and right eye images of same person. Although iris recognition system has achieved good performance, but it is affected by the quality of input images. So, eye image check algorithm, which can select the good quality image is very important. The proposed system is composed of four steps. At the first step, both eye images are captured at the same time. At the second step, the eye image check algorithm picks out noisy and counterfeit data between both eye images and offer a good qualified image to the next step. At the third step, Daubechies' Wavelet is used as a feature extraction method. Finally, Support Vector Machines(SVM) and Euclidian distance are used as classification methods. Experiment results involve 1694 eye images of 111 different people and the best accuracy rate of 99.1%.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsDavid Zhang, Anil K. Jain
PublisherSpringer Verlag
Pages450-457
Number of pages8
ISBN (Print)3540221468, 9783540221463
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3072
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fingerprint

Dive into the research topics of 'Multi-unit iris recognition system by image check algorithm'. Together they form a unique fingerprint.

Cite this