Title :
Coal and Coal Gangue Separation Based on Computer Vision
Author :
Li, Wenhui ; Wang, Ying ; Fu, Bo ; Lin, Yifeng
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Abstract :
We consider the problem of automatically separating coal and coal gangue based on computer vision and design a coal and coal gangue separation system framework based on video. Grayscale histogram, fractal dimension and energy value are extracted as ore features. Then we design a 4-layer Levenberg Marquart BP Neural Network to implement multi-feature fusion. Test results demonstrate that the system has well performance on separation accuracy and its processing speed achieves real-time. It can be used in automatic statistics for open-pit coal output. Moreover, the extended feature vector can be used in coal separation on conveyor belt combined with other automation technology.
Keywords :
backpropagation; coal; computer vision; image fusion; mining industry; neural nets; production engineering computing; video signal processing; 4-layer Levenberg Marquart BP neural network; Grayscale histogram; automatic statistics; automation technology; coal gangue separation system framework; coal mine production; computer vision; conveyor belt; energy value; extended feature vector; fractal dimension; multifeature fusion; open-pit coal output; ore features; video; Feature extraction; Fractals; Gray-scale; Pixel; Training; Wavelet transforms; advanced Differential Box Counting; coal gangue separation; computer vision; lifting wavelet transform; pattern recognition;
Conference_Titel :
Frontier of Computer Science and Technology (FCST), 2010 Fifth International Conference on
Conference_Location :
Changchun, Jilin Province
Print_ISBN :
978-1-4244-7779-1
DOI :
10.1109/FCST.2010.78
