Natural Scene Segmentation Based on Information Fusion and Homogeneity Property

DOI

10.2991/jcis.2006.263How to use a DOI?

Keywords

image segmentation, homogeneity, color feature, texture feature, information fusion, HSOM.

Abstract

This paper presents a novel approach to natural scene segmentation. It uses both color and texture features in cooperation to provide comprehensive knowledge about every pixel in the image. A novel scheme for the collection of training samples, based on homogeneity, is proposed. Natural scene segmentation is carried out using a two-stage hierarchical self-organizing map (HSOM). The proposed method confirms that the sample selection based on homogeneity and the self-learning ability and adaptability of the HSOM, coupled with the information fusion mechanism, can lead to good segmentation result, which is validated by experiments on a variety of natural scene images.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Heng-Da Cheng
AU  - Manasi Datar
AU  - Wen Ju
PY  - 2006/10
DA  - 2006/10
TI  - Natural Scene Segmentation Based on Information Fusion and Homogeneity Property
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.263
DO  - 10.2991/jcis.2006.263
ID  - Cheng2006/10
ER  -