Effectiveness evaluation of iris segmentation by using geodesic active contour (GAC)

Yuan Tsung Chang, Timothy K. Shih, Yung Hui Li, W. G.C.W. Kumara

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

A novel iris segmentation technique based on active contour is proposed in this paper. Our approach uses innovative algorithms, including two important ones, pupil segmentation and iris circle calculation. With our algorithms, we are able to find the center position and radius of pupil correctly and segment the iris precisely. The accuracy of our proposed method for ICE dataset is around 92% and also reached high accuracy level of 79% for UBIRIS. Our results demonstrate that the proposed iris segmentation method can perform well with high accuracy and better efficacy for Iris segmentation in images. Through a relatively high-performance algorithm to further cut up the round out the picture of the pupil conversion cutting growth square picture in order to make the judgment for biometric applications.

Original languageEnglish
Pages (from-to)1628-1641
Number of pages14
JournalJournal of Supercomputing
Volume76
Issue number3
DOIs
StatePublished - 1 Mar 2020

Keywords

  • Active contour
  • Biometrics
  • Iris segmentation

Fingerprint

Dive into the research topics of 'Effectiveness evaluation of iris segmentation by using geodesic active contour (GAC)'. Together they form a unique fingerprint.

Cite this