Roxana Flores-Quispe and Yuber Velazco-Paredes, Universidad Nacional de San Agustín, Perú

This paper proposes a method based on Multitexton Histogram (MTH) descriptor to recognize and classificate eight different human parasite eggs: Ascaris, Uncinarias, Trichuris, Hymenolepis Nana, Dyphillobothrium-Pacificum, Taenia-Solium, Fasciola Hepática and EnterobiusVermicularis identifying 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 co-occurrence 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.

Human Parasite Eggs, Multitexton Histogram descriptor, Textons