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Malaria Parasite Classification using energy based KNN Classifier
Author(s) -
R Charanya,
J. Josphin Mary,
G. Sridevi,
V. Shanthi
Publication year - 2020
Publication title -
european journal of molecular and clinical medicine
Language(s) - English
Resource type - Journals
ISSN - 2515-8260
DOI - 10.31838/ejmcm.07.09.149
Subject(s) - malaria , parasite hosting , classifier (uml) , artificial intelligence , pattern recognition (psychology) , computer science , machine learning , biology , immunology , world wide web
Plasmodium is a type of unicellular eukaryote compulsory for vertebrates or insect parasites. The early diagnosis is required for malaria. In this study, the automatic classification of malaria system is discussed. Initially, the input images are given to gaussian filter, then energy feature is used for feature extraction and K-Nearest Neighbor (KNN) classifier is used for classification. The performance of malaria system produces the specificity of classification 93%using KNN classifier.

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