We describe an approach of automatic feature extraction for shape characterization of seven distinct species of Eimeria, a protozoan parasite of domestic fowl. We used digital images of oocysts, a round-shaped stage presenting inter-specific variability. Three groups of features were used: curvature characterization, size and symmetry, and internal structure quantification. Species discrimination was performed with a Bayesian classifier using Gaussian distribution. A database comprising 3891 micrographs was constructed and samples of each species were employed for the training process. The classifier presented an overall correct classification of 85.75%. Finally, we implemented a real-time diagnostic tool through a web interface, providing a remote diagnosis front-end. © 2007 Pattern Recognition Society.