Malaria caused by Plasmodium parasites is a life-threatening disease in humans, transmitted through the bite of an infected Anopheles mosquito. The most common technique for detecting malaria parasites is Giemsa stained blood smear on optical microscopes. However, conventional microscopy has proved inefficient, because this technique is often time-consuming while the results of the analysis are dependent on the technical's level and difficult to reproduce. Many studies have been proposed to replace diagnostic techniques based on the support of computer vision. In this review, the authors briefly presented the typical results of recent developments in the computer field to support the diagnosis of malaria parasites. The process of diagnosis and identification of malaria parasites, which included image standardisation, segmentation of blood cells and parasites, feature extraction and classification of specific features, was also introduced in this paper. Finally, the authors discussed existing challenges together with proposing research directions to apply automatic diagnostic methods of malaria parasites in Vietnam.