Flotation froth image segmentation based on highlight correction and parameter adaptation
Liang, Xiu Man; Tian, Tong; Liu, Wen Tao; Niu, Fu Sheng
ABSTRACT:
The level of automation employed in flotation production is relatively low. In an actual concentrator, operators use their judgment to adjust the production state based on the visual characteristics of the flotation froth surface. There are shortcomings, such as strong subjectivity and lagging process operation, that easily cause the waste of manpower and material resources. Machine vision technology is introduced to replace human visualization, achieving a quantitative description of the visual characteristics of the froth surface. The state variable parameters are provided for the identification of the flotation conditions.
Full-text paper:
Mining, Metallurgy & Exploration, https://doi.org/10.1007/s42461-019-00137-0
HOW CAN YOU READ THE FULL TEXT OF MME PAPERS?
Follow these easy steps if you are an SME member:
-
Go to
www.smenet.org/login
. Sign in with your email address and password.
-
Hover your mouse over “Publications and Resources” in the top banner. Click on “Mining, Metallurgy & Exploration (MME) Journal” in the pull-down menu.
-
Scroll down and click on the “Read the MME Journal Online” button, which will take you to the Springer site as an SME member who is eligible for free access. (To see published papers on the Springer site, click on “Browse Volumes & Issues” in the blue banner.)
If you are not an SME member, go to
https://www.springer.com/engineering/journal/42461
for paid access. Or join SME at
www.smenet.org/join
