Open AccessMalaria Detection Using Local Composition Pattern
Author(s) -
J. A. Ovi,
M. E. Haque,
Abu Kalam,
S. A. Jarin,
Mohsen Ali,
Mahamudul Hasan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1803/1/012014
Subject(s) - malaria , blood smear , anopheles , biting , plasmodium falciparum , parasite hosting , artificial intelligence , computer science , medicine , immunology , biology , ecology , world wide web
Malaria is a major global health problem. Every year thousands of people have been died because of this harmful disease. It is a life-threatening disease that is triggered by the “night-biting” mosquitoes known as the Anopheles mosquitoes. They normally bite at day time. In this paper, to detect malaria parasite in the bloodstream, an image processing algorithm has been developed. Our proposed approach can classify malaria-infected images from patient’s blood samples by extracting red blood cells (RBCs) from the images. Malaria detection using Local Composite Pattern (LBP) outperforms in comparison with the existing traditional approaches.