Feature-Weighted Mountain Method with Its Application to Color Image Segmentation

DOI

10.2991/ijcis.2011.4.5.23How to use a DOI?

Keywords

Mountain method; Feature weight; Color image segmentation.

Abstract

In this paper, we propose a feature-weighted mountain clustering method. The proposed method can work well when there are noisy feature variables and could be useful for obtaining initial estimat of cluster centers for other clustering algorithms. Results from color image segmentation illustrate the proposed method actually produces better segmentation than previous methods.

Copyright

© 2011, 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  - JOUR
AU  - Wen-Liang Hung
AU  - Miin-Shen Yang
AU  - Jian Yu
AU  - Chao-Ming Hwang
PY  - 2011
DA  - 2011/09/01
TI  - Feature-Weighted Mountain Method with Its Application to Color Image Segmentation
JO  - International Journal of Computational Intelligence Systems
SP  - 1002
EP  - 1011
VL  - 4
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.5.23
DO  - 10.2991/ijcis.2011.4.5.23
ID  - Hung2011
ER  -