Characterisation of flotation froth colour and structure by machine vision

被引:62
作者
Bonifazi, G
Serranti, S
Volpe, F
Zuco, R
机构
[1] Univ Roma La Sapienza, Dipartimento Ingn Chim Mat Mat Prime & Met, I-00184 Rome, Italy
[2] Euroimage SpA, Rome, Italy
关键词
flotation process; froth colour; froth structure; image processing;
D O I
10.1016/S0098-3004(00)00152-7
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
It is well known and well recognised that flotation is a process that is complex to monitor and study if a classical approach based on the evaluation of the signals resulting from sensors is adopted. Sensors are usually strategically positioned in the bank cells and detect global process variables such as pH, reagent addition, froth level, on-stream chemical analysis, particle size distribution, etc. In the last ten years several studies have been carried out with the main goal to utilise imaging techniques to detect froth bubbles characteristics and to evaluate the flotation process performance. In this paper an approach of this type is described. More specifically, image processing techniques to automatically measure the colour and the structure of the froth bubbles are presented and the results are discussed. All the investigations are carried out on digital sample images collected in an industrial flotation plant operating in steady-state conditions. The colour analysis is performed on the whole surface of the froth images considering different colour reference systems (RGB, HSV, HSI); the morphological measurements are obtained after the application of selected enhancement and segmentation techniques, necessary to consider the bubbles as separate domains. The multiple correlation analysis performed between froth mineral concentrations (Cu, MgO, Zn and Pb content) and the extracted colour and structure parameters are good in most situations. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:1111 / 1117
页数:7
相关论文
共 19 条
[1]  
Beucher S., 2018, Mathematical morphology in image processing, P433, DOI DOI 10.1201/9781482277234-12
[2]   Prediction of complex sulfide flotation performances by a combined 3D fractal and colour analysis of the froths [J].
Bonifazi, G ;
Massacci, P ;
Meloni, A .
MINERALS ENGINEERING, 2000, 13 (07) :737-746
[3]  
BONIFAZI G, 2000, P 21 INT MIN PROC C, P178
[4]  
BONIFAZI G, 2000, UNPUB INT J MINING P
[5]  
BONIFAZI G, 1998, 4 INT C QUAL CONTR A, P131
[6]  
BONIFAZI G, 2000, P 21 INT MIN PROC C, P39
[7]  
CIPRIANO A, 1997, P 20 INT MIN PROC C, P281
[8]  
CIPRIANO A, 1995, P INT C SIGN PROC AP, P23
[9]   TEXTURAL FEATURES FOR IMAGE CLASSIFICATION [J].
HARALICK, RM ;
SHANMUGAM, K ;
DINSTEIN, I .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1973, SMC3 (06) :610-621
[10]  
Hargrave J.M., 1998, COAL PREP, V19, P69, DOI DOI 10.1080/07349349808945574