Identification of Giemsa Staind of Malaria Using K-Means Clustering Segmentation Technique

被引：0

作者：

Haryanto, Edy Victor S. ^{[1
,2
]}

Mashor, M. Y. ^{[2
]}

Nasir, A. S. Abdul ^{[2
]}

Mohamed, Zeehaida ^{[3
]}

机构：

[1] Univ Potensi Utama, Fac Engn & Comp Sci, Jl KL Yos Sudarso Km 6,5 3 A, Medan 20241, Indonesia

[2] Univ Malaysia Perlis, Sch Mechatron Engn, Arau 02600, Malaysia

[3] Univ Sains Malaysia, Dept Patol Microbiol & Parasitol, Kubang Kerian 16150, Kelantan, Malaysia

来源：

2018 6TH INTERNATIONAL CONFERENCE ON CYBER AND IT SERVICE MANAGEMENT (CITSM) | 2018年

关键词：

Image Processing; Segmentation Technique; Giemsa Staind; Malaria; K-means Clustering Algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Malaria is disease the most common in the world. The disease is caused by mosquito bites anywhere. The identification process will take some time to deliver maximum results. One of the techniques used to identification image of blood cell is segmentation, the technique used in this study is a K-Means. K-means clustering algorithm can be combined with segmentation technique to obtain the identification of malaria virus. In on this study K-Means clustering segmentation techniques capable of providing identification automation with Giemsa staining of malaria, and the results of blood that is infected will be directly identified.

引用

页码：268 / 271

页数：4

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