Research Progress of Flotation Froth Image Feature Extraction Method
As a tool for equipment operators,machine vision has been widely used in the monitoring of froth flota-tion equipment.A predictive identification model has been developed,utilizing a froth image dataset,with primary froth characteristic parameters as inputs and flotation indicators like grade and recovery as outputs.Depending on the necessity for manual extraction of flotation froth image features,the feature extraction algorithms can be divided into two main categories:one is traditional manual feature extraction methods that rely on aspects such as color and morphological features,and the other is automatic feature extraction methods grounded in deep neural net-works.This paper summarizes the research progress in the area of flotation froth image feature extraction algorithms over recent years,while also critically examining the advantages and drawbacks of various methods it has certain guiding value for the curront difficulty in manually indentifying foam status and realizing flotation automation to im-prove flotation efficiency.
froth flotationfroth imagemachine visionfroth image features
国家科技期刊平台
NSTL
万方数据
