Natural Scene Segmentation Based on Information Fusion and Homogeneity Property
Heng-Da Cheng 0, Manasi Datar, Wen Ju
0Computer Science Department, Utah State University
Available Online October 2006.
- https://doi.org/10.2991/jcis.2006.263How to use a DOI?
- image segmentation, homogeneity, color feature, texture feature, information fusion, HSOM.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/jcis.2006.263 ID - Cheng2006/10 ER -