Coarse iris classification based on box-counting method

Li Yu, Kuanquan Wang, Dapeng Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

This paper proposes a novel algorithm for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases, and the proportions of these categories in our database are 5.50%, 38.54%, 21.79% and 34.17%. The iris images are classified with the double threshold algorithm, which classifies iris images with an accuracy of 94.61%. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.
Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing 2005, ICIP 2005
Pages301-304
Number of pages4
Volume3
DOIs
Publication statusPublished - 1 Dec 2005
EventIEEE International Conference on Image Processing 2005, ICIP 2005 - Genova, Italy
Duration: 11 Sep 200514 Sep 2005

Conference

ConferenceIEEE International Conference on Image Processing 2005, ICIP 2005
CountryItaly
CityGenova
Period11/09/0514/09/05

Keywords

  • Box counting
  • Coarse classification
  • Fractal dimension
  • Iris image

ASJC Scopus subject areas

  • Engineering(all)

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