X-ray Coal Purity Examination Base on Particle Swarm Optimization Clustering

DOI

10.2991/icetis-13.2013.144How to use a DOI?

Keywords

coal purity; particle swarm; clustering analysis; X-ray; fitness function

Abstract

the paper mainly researched on the usage of particle swarm in image clustering. A fitness function is designed based on the principle of minimum in cluster distance and maximum between cluster distance. And particle swarm optimization, which is combined with fuzzy clustering, is used in image clustering. A system of X-ray coal image purity detection is developed and tested. According to the intensity distribution of X-ray images, an area of interest is selected based on Gaussian distribution property which greatly cut down the data to be processed. On the basis of that, particle swarm clustering is applied, and impurities are selected based on the fact that impurities are always tiny intensity elements. Experiments show that the approach is effective.

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  - Hao Long
AU  - Na Huo
AU  - Yong Yang
AU  - Bencheng Yu
PY  - 2013/06
DA  - 2013/06
TI  - X-ray Coal Purity Examination Base on Particle Swarm Optimization Clustering
BT  - Proceedings of the 2013 the International Conference on Education Technology and Information System (ICETIS 2013)
PB  - Atlantis Press
SP  - 642
EP  - 645
SN  - 1951-6851
UR  - https://doi.org/10.2991/icetis-13.2013.144
DO  - 10.2991/icetis-13.2013.144
ID  - Long2013/06
ER  -