• Navya N
• Meghashree A C

The Malaria is a genuine irresistible infection. As indicated by the World Health Organization, it is in charge of about one million passing’s every year. There are different procedures to analyze malaria of which manual microscopy is viewed as the best quality level. Malaria is mosquito-borne blood illness brought about by parasites of the class Plasmodium. A specialist examine the microscope image and detects weather the person is infected or not, this is tedious procedure and has various problems. This paper, presents an image processing technique that can be used to detect the malaria disease. The method mainly uses Otsu thresholding, GLCM, later Machine Learning to learn, identify and decide the sorts of infected cells as indicated by its highlights, for this SVM is used.

Malaria, plasmodium, RBC, Otsu thresholding, GLCM, SVM.

"Enhanced detection of Malaria disease using Image processing and Machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.351-354, June-2019, Available :http://www.jetir.org/papers/JETIR1906832.pdf

"Enhanced detection of Malaria disease using Image processing and Machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp351-354, June-2019, Available at : http://www.jetir.org/papers/JETIR1906832.pdf