Recognition of airborne fungi spores in digital microscopic images

We propose and evaluate a method for the recognition of airborne fungi spores. We use a model-based object recognition method to identify spores in a digital microscopic image. We do not use the gray values of the model, but use the object edges instead. The similarity measure measures the average angle between the vectors of the template and the object. Model generation is done semi-automatically by manually tracing the object, automatic shape alignment, similarity calculation, clustering and prototype calculation.