K - means multi-threshold image segmentation based on firefly algorithm

DOI

10.2991/icmt-13.2013.17How to use a DOI?

Keywords

Firefly algorithm; K-Means algorithm; multi-threshold; image segmentation

Abstract

This paper presents multi-threshold image segmentation approach based on K-means and firefly algorithm. This approach first use the firefly algorithm based on the characteristics of the groups search for optimization to obtain threshold as K-means initial clustering center. It could effectively overcome the problem that K-means algorithm is sensitive to the initial center. Compared with the traditional K-means algorithm, the experiment results show that the proposed approach hasfaster run time and higher efficiency. Moreover, the proposed method also had better segmentation result and get a better peak signal-to-noise ratio (PSNR) than the traditional FFCM and PSO-FFCM.

Copyright

© 2013, 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  - Yang Jie
AU  - Yang Yang
AU  - Yu Weiyu
AU  - Feng Jiuchao
PY  - 2013/11
DA  - 2013/11
TI  - K - means multi-threshold image segmentation based on firefly algorithm
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 134
EP  - 142
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.17
DO  - 10.2991/icmt-13.2013.17
ID  - Jie2013/11
ER  -