Texture enhancement of iris images acquired under natural light

Boyan Hou, Yuqing He*, Mengmeng Liang, Xue Wang

*Corresponding author for this work

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

Abstract

The iris image acquired under natural light may be degraded by non-uniform illumination, which results in the iris texture’s low resolution and low contrast. The recognition accuracy may be affected. This paper describes a method for enhancing the iris textures on the V channel of HSV space. The enhancement has two steps. First, the image is divided into small blocks and luminance enhancement is carried out in each block by using nonlinear transfer function and bilinear interpolation. Secondly, contrast enhancement by multi-scale Gaussian convolution is applied to improve the quality of the image. We test the proposed method on UBIRIS.v2 database. Experimental results show that the proposed method has better texture enhancement performance and can achieve higher recognition accuracy.

Original languageEnglish
Title of host publicationBiometric Recognition - 10th Chinese Conference, CCBR 2015, Proceedings
EditorsJucheng Yang, Zhenan Sun, Shiguang Shan, Jinfeng Yang, Jianjiang Feng, Weishi Zheng
PublisherSpringer Verlag
Pages373-380
Number of pages8
ISBN (Print)9783319254166
DOIs
Publication statusPublished - 2015
Event10th Chinese Conference on Biometric Recognition, CCBR 2015 - Tianjin, China
Duration: 13 Nov 201515 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9428
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Chinese Conference on Biometric Recognition, CCBR 2015
Country/TerritoryChina
CityTianjin
Period13/11/1515/11/15

Keywords

  • Contrast enhancement
  • Gaussian convolution
  • Iris recognition
  • Luminance enhancement
  • Natural light
  • Nonlinear transfer function

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