Textons of Irregular Shape to Identify Patterns in the Human Parasite Eggs

This paper proposes a method based on Multitexton Histogram (MTH) descriptor to identify patterns in
images of human parasite eggs of the following species: Ascaris, Uncinarias, Trichuris, Hymenolepis
Nana, Dyphillobothrium-Pacificum, Taenia-Solium, Fasciola Hepática and Enterobius-Vermicularis.
These patterns are represented by textons of irregular shapes in their microscopic images. This proposed
method could be used for diagnosis of Parasitic disease and it can be helpful especially in remote places.
This paper includes two stages. In the first a feature extraction mechanism integrates the advantages of cooccurrence matrix and histograms to identify irregular morphological structures in the biological images
through textons of irregular shape. In the second stage the Support Vector Machine (SVM) is used to
classificate the different human parasite eggs. The results were obtaining using a dataset with 2053 human
parasite eggs images achieving a success rate of 96,82% in the classification. In addition, this research
shows that the proposed method also works with natural images.