The present invention relates generally to the field of computer-based image recognition. More particularly, the invention relates to methods and systems for the identification, and optionally the quantitation of, discrete objects of biological origin such as cells, cytoplasmic structures, parasites, parasite ova, and the like which are typically the subject of microscopic analysis. The inventionmay be embodied in the form of a method for training a computer to identify a target biological material in a sample. The method may include accessing a plurality of training images, the training images being obtained by light microscopy of one or more samples containing a target biological material and optionally a non-target biological material. The training images are cropped by a human or a computer to produce cropped images, each of which shows predominantly the target biological material. A human then identifies the target biological material in each of the cropped images where identification is possible, and associating an identification label with each of the cropped images where identification was possible. A computer-implemented feature extraction method is then applied to each labelled cropped image. A computer-implemented learning method is then applied to each labelled cropped image to associate extracted features of a biological material with a target biological material.