Abstract: The traditional system for detecting the infection has been the manual process of diagnosing the stained slides under a microscope. This manual process might consume more time for producing the results and the availability of medical experts is not always assured. Considering this as the primary concern we proposed a strategy which limits the human error while recognizing the presence of malarial parasite in the blood sample by using Image Processing. Hence by automating the diagnosis process, results can be acquired relatively quicker and more accuracy can be expected. The technologies and techniques to patently extract the required features and efficiently classify the infected samples are surveyed. This paper presents a survey of various approaches to automate the detection and classification of infected and uninfected cells.