Towards automation of palynology 3: pollen pattern recognition using Gabor transforms and digital moments

Abstract

Abstract The classification of pollen grains using texture information in combination with shape features is presented in this paper. The surface texture of pollen is characterised by using Gabor transforms, the geometric shape is described by using moment invariants, and the pollen grains are classified by an artificial neural network. In an experiment with five types of pollen grains, more than 97% of samples are correctly classified. Copyright © 2004 John Wiley & Sons, Ltd.