Journal ArticleDOI
Online monitoring and control of froth flotation systems with machine vision: A review
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TLDR
Machine vision has been used to extract froth characteristics, both physical (e.g. bubble size) and dynamic (froth velocity) from digital images and present these results to operators and/or use the results as inputs to process control systems.About:
This article is published in International Journal of Mineral Processing.The article was published on 2010-09-15. It has received 203 citations till now. The article focuses on the topics: Machine vision & Computer technology.read more
Citations
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Journal ArticleDOI
A review of froth flotation control
B. Shean,Jan J. Cilliers +1 more
TL;DR: In this article, a review of the four essential levels of process control (instrumentation, base level flotation control, advanced flotation, and optimising flotation) is presented.
Journal ArticleDOI
Machine learning applications in minerals processing: A review
John T. McCoy,Lidia Auret +1 more
TL;DR: This review aims at equipping researchers and industrial practitioners with structured knowledge on the state of machine learning applications in mineral processing with suggestions on data collection, technique comparison, industrial participation, cost-benefit analyses and the future of mineral engineering training.
Journal ArticleDOI
Flotation froth image recognition with convolutional neural networks
Y. Fu,Chris Aldrich +1 more
TL;DR: Three pretrained neural networks architectures to estimate froth grades from industrial image data, namely AlexNet, VGG16 and ResNet is considered and, in its pretrained format, AlexNet outperformed previously proposed methods by a significant margin.
Journal ArticleDOI
Ore grade estimation by feature selection and voting using boundary detection in digital image analysis
Claudio A. Perez,Pablo A. Estevez,Pablo A. Vera,Luis E. Castillo,Carlos M. Aravena,Daniel A. Schulz,Leonel E. Medina +6 more
TL;DR: This paper presents a new method to improve rock classification using digital image analysis, feature selection based on mutual information and a voting process to take into account boundary information and shows that the RMSE on rock composition classification on a test database decreased 8.8% by using the proposed voting method with the automatic segmentation with respect to direct sub-image classification.
Journal ArticleDOI
Prediction of the metallurgical performances of a batch flotation system by image analysis and neural networks
TL;DR: In this article, the relationship between the process conditions and the froth features as well as the process performance in the batch flotation of a copper sulfide ore is discussed and modeled.
References
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Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
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A review on image segmentation techniques
Nikhil R. Pal,Sankar K. Pal +1 more
TL;DR: Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches, which addresses the issue of quantitative evaluation of segmentation results.
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A survey on image segmentation
King-Sun Fu,J. K. Mui +1 more
TL;DR: This survey summarizes some of the proposed segmentation techniques in the area of biomedical image segmentation, which fall into the categories of characteristic feature thresholding or clustering and edge detection.
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Image texture analysis: methods and comparisons
TL;DR: An overview of several different approaches to image texture analysis is provided and insight into their space/frequency decomposition behavior is used to show why they are generally considered to be state of the art in texture analysis.
Journal ArticleDOI
Flotation froth monitoring using multiresolutional multivariate image analysis
TL;DR: In this paper, a multiresolutional multivariate image analysis (MR-MIA) is proposed for the monitoring and control of flotation processes, which can handle spatial (i.e., morphological) and color information of froth images efficiently, and is inherently robust to image quality and lighting conditions.