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 language | English |
|---|---|
| Title of host publication | Proceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014 |
| Publisher | IEEE Computer Society |
| Pages | 102-106 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509004218 |
| DOIs | |
| State | Published - 1 Sep 2016 |
| Event | 33rd International Conference of the Chilean Computer Science Society, SCCC 2014 - Talca, Maule, Chile Duration: 12 Nov 2014 → 14 Nov 2014 |
Publication series
| Name | Proceedings - International Conference of the Chilean Computer Science Society, SCCC |
|---|---|
| Volume | 2016-September |
| ISSN (Print) | 1522-4902 |
Conference
| Conference | 33rd International Conference of the Chilean Computer Science Society, SCCC 2014 |
|---|---|
| Country/Territory | Chile |
| City | Talca, Maule |
| Period | 12/11/14 → 14/11/14 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- CBIR
- Human Parasite Eggs
- Multitexton Histogram descriptor
- Textons
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