CQUniversity
Browse
cqu_5678+ATTACHMENT01+ATTACHMENT01.4.pdf (1.56 MB)

Unsupervised clustering for electrofused magnesium oxide sorting

Download (1.56 MB)
conference contribution
posted on 2017-12-06, 00:00 authored by Wai Keung Pun, A B M Shawkat Ali
This research is concentrated on using un-supervised learning technique and digital image processing to cluster mineral materials, Electrofused Magnesia Oxide specifically,for industry automation. We proposed a technique to construct an image database by generating datafrom images using a digital image process. This is based on a simple histogram mode and intensity deviation. A group of two popular clustering algorithms has been tested to develop an automatic system for industry. We have concluded that the best suited algorithm for this application in the mineral industry from this group of two algorithms is the k-means algorithm.

History

Start Page

698

End Page

702

Number of Pages

5

Start Date

2009-01-01

ISBN-13

9781424448708

Location

Hong Kong

Publisher

IEEE

Place of Publication

USA

Peer Reviewed

  • Yes

Open Access

  • No

Era Eligible

  • Yes

Name of Conference

IEEE International Conference on Industrial Engineering and Engineering Management