Automatic diatom recognition on digital images

Diatoms are a large group of microscopic algae that grow as independent organisms or in small colonies and are characterized by a silica cell wall. They are widely used as ecosystem health and evolution tracers. One of the their most important characteristic is the fact that they vary their shape among different families and this makes possible its classification using pattern recognition techniques. In this paper, we describe a new process based on determining the invariant moments of the objects presented in a digital image to classify them according to the different families. We present a technique to segment the diatoms using a new thresholding technique, contour tracing and a recognition process. Finally, the results are presented.