This work describes a system for detecting and classifying malaria parasites in images of Giemsa stained blood slides in order to evaluate the parasitaemia of the blood. The first aim of our system is to detect the parasites by means of an automatic thresholding based on a morphological approach. Then we propose a morphological method to cell image segmentation based on grey scale granulometries and openings with disk-shaped elements, flat and hemispherical, that is more accurate than the classical watershed-based algorithm. The last step of the system is classifying the parasites by morphological skeleton.