Transactions of Nonferrous Metals Society of China The Chinese Journal of Nonferrous Metals

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Transactions of Nonferrous Metals Society of China

Vol. 24    No. 8    August 2014

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Rapid vision-based system for secondary copper content estimation
Hong-wei ZHANG1, Zhi-qiang GE1, Xiao-feng YUAN1, Zhi-huan SONG1, Ling-jian YE1,2

1. State Key Laboratory of Industrial Control Technology, Institute of Industrial Process Control,
Zhejiang University, Hangzhou 310027, China;
2. Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, China

Abstract:A vision-based color analysis system was developed for rapid estimation of copper content in the secondary copper smelting process. Firstly, cross section images of secondary copper samples were captured by the designed vision system. After the preprocessing and segmenting procedures, the images were selected according to their grayscale standard deviations of pixels and percentages of edge pixels in the luminance component. The selected images were then used to extract the information of the improved color vector angles, from which the copper content estimation model was developed based on the least squares support vector regression (LSSVR) method. For comparison, three additional LSSVR models, namely, only with sample selection, only with improved color vector angle, without sample selection or improved color vector angle, were developed. In addition, two exponential models, namely, with sample selection, without sample selection, were developed. Experimental results indicate that the proposed method is more effective for improving the copper content estimation accuracy, particularly when the sample size is small.


Key words: secondary copper; copper content estimation; sample selection; color vector angle; least squares support vector regression

ISSN 1004-0609
CN 43-1238/TG

ISSN 1003-6326
CN 43-1239/TG

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