Ethnicity Prediction and Classification from Iris Texture Patterns: A Survey on Recent Advances

Gugulethu Phumzile Mabuza-Hocquet, Fulufhelo Nelwamondo, Tshilidzi Marwala

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

6 Citations (Scopus)

Abstract

The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research in iris biometrics has been focused on using iris features for individual recognition and verification, very little work has been focused on using iris texture patterns to determine other demographic attributes of individuals such as ethnicity and gender. The aim of this paper is to consolidate most of the work done by researchers, through delving and comparing the different techniques, algorithms and results achieved over the last decade.

Original languageEnglish
Title of host publicationProceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
EditorsMary Yang, Hamid R. Arabnia, Leonidas Deligiannidis, Leonidas Deligiannidis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages818-823
Number of pages6
ISBN (Electronic)9781509055104
DOIs
Publication statusPublished - 17 Mar 2017
Event2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 - Las Vegas, United States
Duration: 15 Dec 201617 Dec 2016

Publication series

NameProceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

Conference

Conference2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
Country/TerritoryUnited States
CityLas Vegas
Period15/12/1617/12/16

Keywords

  • iris ethnic classification
  • iris feature extraction
  • iris textons
  • iris texture patterns

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Health Informatics
  • Artificial Intelligence
  • Computer Networks and Communications

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