DOIONLINE

DOIONLINE NO - IJAECS-IRAJ-DOIONLINE-6501

Publish In
International Journal of Advances in Electronics and Computer Science-IJAECS
Journal Home
Volume Issue
Issue
Volume-3,Issue-12  ( Dec, 2016 )
Paper Title
Classfication of Malarial Parasite and its Life-Cycle-Stages in Blood Smear
Author Name
Sri Hartati, Agus Harjoko, Rika Rosnelly, Ika Candradewi
Affilition
Department of Computer Science and Electronics, Universitas Gadjah Mada
Pages
89-93
Abstract
A method to classify plasmodium of malaria disease along with its life stage is presented. The geometry and texture features are used as plasmodium features for classification. The geometry features are area and perimeters. The texture features are computed from GLCM matrices. The support vector machine (SVM) classifier is employed for classifying the plasmodium and its life stage into 12 classes. Experiments were conducted using 600 images of blood samples. The SVM with linear kernel gives the accuracy of 57% whereas SVM with RBF kernel yields an accuracy of 99.1%. Index Terms- Malaria, geometry, texture, GLCM, SVM, RBF.
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