FOURIER–MELLIN TRANSFORM FEATURES FOR MALARIA PARASITES CLASSIFICATION USING MICROSCOPIC IMAGES
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 9, Pages 1426-1430
AbstractMalaria is an infectious disease transmitted by mosquitoes that affects humans and other animals. Malaria is responsible for the effects of fever, tiredness, vomiting and headaches. Yellow skin, convulsions, a coma, or death can lead to severe cases. Symptoms usually start 10-15 days after a mosquito is bitten. The early diagnosis is required for malaria. In this study, the automatic classification of malaria system is discussed. Initially, the input images are given to Fourier–Mellin transform for feature extraction and Support Vector Machine (SVM) classifier is used for classification. The performance of malaria system produces the classification accuracy of 92%using SVM classifier.
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