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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Optimal Computer Based Analysis for Detecting Malarial Parasites
verfasst von : S. T. Khot, R. K. Prasad
Erschienen in: Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014
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Malaria poses a serious global health problem and it requires a rapid, accurate diagnosis to control the disease. An image processing algorithm for accurate and rapid automation in the diagnosis of malaria in blood images is developed in this research paper. The image classification system to identify the malarial parasites positively present in thin blood smears is designed, and differentiated into the various species and stages of malaria - falciparum and vivax prevalent in India. Method implemented presents a new approach to image processing in which the detection experiments employed the KNN rule, along with other algorithms such as ANN (Artificial Neural Networks), Zack’s thresholding and Linear Programming and Template matching to find out the optimal classifier for detection and classification of malarial parasites with its stages.