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

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...

Full description

Saved in:
Bibliographic Details
Published in:Journal of quaternary science 2004-12, Vol.19 (8), p.763-768
Main Authors: Zhang, Y., Fountain, D. W., Hodgson, R. M., Flenley, J. R., Gunetileke, S.
Format: Article
Language:English
Subjects:
Gabor transforms
moment invariants
neural network
pollen analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0267-8179
1099-1417
DOI:10.1002/jqs.875