Abstract :
Malaria is a critical disease for which the instant detection is essential so as to control it. Microscopes are used to detect the disease and pathologists use the manual technique because of which there is several chance of incorrect detection being made regarding the disease. If the incorrect detection is made then the disease can turn into more difficult situation. So the study relating to the computerized detection is done in this paper that will facilitate in instant detection of the disease to some level. An image processing scheme is capable to enhance outcome of malaria parasite cell detection. In image processing image consistency is very essential to acquire correct result. Therefore to increase the correctness of the malaria detection system, we proposed new image processing based system which includes two algorithms. One is Haar wavelet algorithm for image transformation and other is K nearest neighbor algorithm for image classification. This system helps to reduce time as well as offer the better accuracy to detect Malaria to some degree. Kanchan N. Poharkar | Dr. S. A. Ladhake "Implementation of Malaria Parasite Detection System Using Image Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: https://www.ijtsrd.com/papers/ijtsrd12798.pdf Paper URL: http://www.ijtsrd.com/computer-science/other/12798/implementation-of-malaria-parasite-detection-system-using-image-processing/kanchan-n-poharkar
Keyword :
Malaria, Parasite detection, Haar wavelet transform, Feature extraction, KNN classifier