Automatic Identification of Human Parasite Eggs Based on Multitexton Histogram Retrieving the Relationships between Textons

Roxana Flores Quispe, Yuber Elmer Velazco Paredes, Raquel Esperanza Patino Escarcina, Cesar A.Beltran Castanon

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

2 Scopus citations

Abstract

In order to identify the parasitic diseases, this paper propose the automatic identification of Human Parasite Eggs to eight different species: Ascaris, Uncinarias, Trichuris, Dyphillobothrium-Pacificum, Taenia-Solium, Fasciola Hep&x00E1;ticaand Enterobius-Vermicularis from their microscopic imagesbased on Multitexton Histogram - MTH using new structuresof textons. This proposed system includes two stages. In firststage, a feature extraction mechanism that is based on MTHdescriptor retrieving the relationships between textons. In second stage, an CBIR system has been implemented in orden to detect their correct species of helminths. Finally, simulation results show overall success rates of 94,78% in the detection.

Original languageEnglish
Title of host publicationProceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014
PublisherIEEE Computer Society
Pages102-106
Number of pages5
ISBN (Electronic)9781509004218
DOIs
StatePublished - 1 Sep 2016
Externally publishedYes
Event33rd International Conference of the Chilean Computer Science Society, SCCC 2014 - Talca, Maule, Chile
Duration: 12 Nov 201414 Nov 2014

Publication series

NameProceedings - International Conference of the Chilean Computer Science Society, SCCC
Volume2016-September
ISSN (Print)1522-4902

Conference

Conference33rd International Conference of the Chilean Computer Science Society, SCCC 2014
Country/TerritoryChile
CityTalca, Maule
Period12/11/1414/11/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • CBIR
  • Human Parasite Eggs
  • Multitexton Histogram descriptor
  • Textons

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