Identification of Malaria Infection using HSV Colour Model and Dynamic Thresholding with Image Binarization

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S. K. B. Sanjay Nag, “Identification of Malaria Infection using HSV Colour Model and Dynamic Thresholding with Image Binarization”, ijmhs, vol. 6, no. 1, Feb. 2016.
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Abstract

Malaria is a mosquito borne infectious disease of humans and other animals caused by unicellular parasitic micro-organism ofplasmodiumgenus underprotozoa.This disease is transmitted through the bite from an infected female Anopheles mosquito. The organism is introduced from its saliva into the host circulatory system. Within the blood stream the parasite travels to the liver where they mature and reproduce.Malaria is a serious global health problem and nearly one million deaths is reported eachyear. Malaria causes symptoms that typically include high fever and headache that under severe infection can progress to coma or death. The disease is prevalent in tropical and subtropical regions around the equator region, including much of sub-Saharan Africa, Asia, and America.  Accurate diagnosis is important to control the disease. There are several diagnostic tools available but microscopic analysis is the gold standard. An image processing method to automate the diagnosis of malaria in blood smear images is proposed in this paper using image segmentation approach for detection of malaria parasite.

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