Identification of Malaria Parasite Using Soft Computing Techniques

Malaria is one of the significant causes of death, every year, around 1 million people worldwide. Although there are some potent methods to cure malaria, the mushrooming growth of malaria cases is for several reasons. A variety of competent diagnostic procedures are to be undertaken to curb the menace. Various traditional methods have been used to diagnose malaria but having so many limitations, so new technology has been developed to overcome traditional methods. This review defines the diagnostic techniques for malaria available currently. This review details the current approach to diagnosing malaria practically and helpfully for the technicians and the patient. These methods have been widely for imaging, image preprocessing, detection of parasites and segmentation of cells, feature computational and automatic classification of a cell. This study examines the malaria detection methods, both traditional and the existing new ways. Image processing through machine learning technology plays a vital role in identifying the parasites.