Ordering of the RGB space with a growing self-organizing network. application to color mathematical morphology

Authors:
Francisco Flórez-Revuelta
Affiliations:
U.S.I. “Informática Industrial y Redes de Computadores Universidad de Alicante, Alicante, Spain
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Year:
2005

Citing 3
Cited 0

Growing cell structures—a self-organizing network for unsupervised and supervised learning

Neural Networks
Total ordering based on space filling curves for multivalued morphology

ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
Self-Organizing Maps

Self-Organizing Maps

Quantified Score

Hi-index	0.00

Visualization

Abstract

Mathematical morphology is broadly used in image processing, but it is mainly restricted to binary or greyscale images. Extension to color images is not straightforward due to the need of application to an ordered space with an infimum and a supremum. In this paper a new approach for the ordering of the RGB space is presented. The adaptation of a linear growing self-organizing network to the three-dimensional color space allows the definition of an order relationship among colors. This adaptation is measured with the topographic product to guarantee a good topology-preservation of the RGB space. Once an order has been established, several examples of application of mathematical morphology operations to color images are presented.