- Tytuł:
- Estimation of copper concentrate grade based on color features and least-squares support vector regression
- Autorzy:
-
Ren, C.
Yang, J.
Liang, C. - Powiązania:
- https://bibliotekanauki.pl/articles/110309.pdf
- Data publikacji:
- 2015
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
concentrate grade
copper concentrate
LS-SVR
color features
microscopic image - Opis:
- In this paper, a new method based on color features of microscopic image and least-squares support vector regression model (LS-SVR) is proposed for indirect measurement of copper concentrate grade. Red, green and blue (RGB), hue and color vector angle were extracted from color microscopic images of a copper concentrate sample and selected for the comparison. Three different estimation models based on LS-SVR were developed using RGB, hue, and color vector angle, respectively. A comparison of three models was carried out through a validation test. The best model was obtained for the hue giving a running time of 30.243 ms, root mean square error of 0.8644 and correlation coefficient value of 0.9997. The results indicated that the copper concentrate grade could be estimated by the LS-SVR model using the hue as input parameter with a satisfactory accuracy.
- Źródło:
-
Physicochemical Problems of Mineral Processing; 2015, 51, 1; 163-172
1643-1049
2084-4735 - Pojawia się w:
- Physicochemical Problems of Mineral Processing
- Dostawca treści:
- Biblioteka Nauki
Artykuł