title: |
Natural Scene Segmentation Based on Information Fusion and Homogeneity Property |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-01-7 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/jcis.2006.263 (how to use a DOI) | |
author(s): |
Heng-Da Cheng, Manasi Datar, Wen Ju |
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corresponding author: |
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publication date: |
October 2006 |
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keywords: |
image segmentation, homogeneity, color feature, texture feature, information fusion, HSOM. |
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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. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |