Fusion of novel iris segmentation quality metrics for failure detection

Thierry Lefevre, Bernadette Dorizzi, Sonia Garcia-Salicetti, Nadege Lemperiere, Stephane Belardi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Segmentation of the iris is one of the key modules of an iris recognition system. For this reason, it is critical to predict failures of this module. In this article we propose a new set of segmentation quality metrics dedicated this problem. We assess the quality of our metrics based on their ability to predict the intrinsic recognition performance of a segmented image. A straightforward fusion procedure then allows generating a global segmentation quality score.

Original languageEnglish
Title of host publicationImage Analysis and Recognition - 10th International Conference, ICIAR 2013, Proceedings
Pages97-106
Number of pages10
DOIs
Publication statusPublished - 26 Sept 2013
Externally publishedYes
Event10th International Conference on Image Analysis and Recognition, ICIAR 2013 - Povoa do Varzim, Portugal
Duration: 26 Jun 201328 Jun 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7950 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Image Analysis and Recognition, ICIAR 2013
Country/TerritoryPortugal
CityPovoa do Varzim
Period26/06/1328/06/13

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