A fast iris image quality evaluation method based on weighted entropy

Yuqing He, Ting Liu*, Yushi Hou, Yuanbo Wang

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

During the image acquisition procedure of an automatic iris recognition system, the iris image with low quality may lead to the personal identification failure in some cases. Therefore it is very important to adopt the image quality evaluation procedure before the image processing. In this paper, we proposed a fast image quality evaluation method based on weighted information entropy combining iris image segmentation through localization. Through this method, we can fast grade the images and pick out the high quality iris images from the video sequence captured by the image acquisition device. Experimental results show that this method can quickly and effectively screen out appropriate images to meet the requirements of the iris recognition algorithm. It can also improve the speed and accuracy of the iris recognition system.

Original languageEnglish
Title of host publicationInternational Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing
DOIs
Publication statusPublished - 2008
EventInternational Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing - Beijing, China
Duration: 9 Sept 200712 Sept 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6623
ISSN (Print)0277-786X

Conference

ConferenceInternational Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing
Country/TerritoryChina
CityBeijing
Period9/09/0712/09/07

Keywords

  • Image segmentation
  • Iris image
  • Quality evaluation
  • Weighted entropy

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