Coal/Gangue Recognition Using Convolutional Neural Networks and Thermal Images

Recognition and separation of Coal/Gangue are important phases in the coal industries for many aspects. This paper addressed the topic of Coal/Gangue recognition and built a new model called (CGR-CNN) based on Convolutional Neural network (CNN) and using thermal images as standard images for Coal/Gangue recognition. The CGR-CNN model has been developed, augmentation principle has been applied in order to increase the dataset and the best experimental results have been achieved (99.36%) learning accuracy and (95.09%) validation accuracy, in the prediction phase (160) new images of coal and gangue (80 for both) have been tested to measure the efficiency of the work, the prediction result comes with (100%) for coal recognition accuracy and (97.5%) gangue recognition accuracy giving an overall prediction accuracy (98.75%).

[1]  Bo Fu,et al.  Coal and Coal Gangue Separation Based on Computer Vision , 2010, 2010 Fifth International Conference on Frontier of Computer Science and Technology.

[2]  Yang Jianguo,et al.  Fast Predicting the Washability of Coal Using Digital Image Processing Method , 2011 .

[3]  Haoxiang Wang,et al.  An Efficient of Coal and Gangue Recognition Algorithm , 2013 .

[4]  Menggang Li,et al.  Separation Between Coal and Gangue Based on Infrared Radiation and Visual Extraction of the YCbCr Color Space , 2020, IEEE Access.

[5]  Zhe Liang,et al.  Automatic Separation System of Coal Gangue Based on DSP and Digital Image Processing , 2011, 2011 Symposium on Photonics and Optoelectronics (SOPO).

[6]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[7]  Sai Ma,et al.  Image Processing Based on Gray Information in Sorting System of Coal Gangue , 2018, 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC).

[8]  Jianqing Zhu,et al.  Automatic Recognition of Coal and Gangue based on Convolution Neural Network , 2017, ArXiv.

[9]  Xiao-Ru Song,et al.  Research on Coal Gangue On-Line Automatic Separation System Based on the Improved BP Algorithm and ARM , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[10]  Man Li,et al.  An Image Recognition Approach for Coal and Gangue Used in Pick-Up Robot , 2018, 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR).

[11]  Hongwei Ma,et al.  Research on Coal Gangue Identification by Using Convolutional Neural Network , 2018, 2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC).

[12]  Yuanyuan Pu,et al.  Image Recognition of Coal and Coal Gangue Using a Convolutional Neural Network and Transfer Learning , 2019, Energies.

[13]  Xian-Min Ma,et al.  Coal Gangue Image Identification and Classification with Wavelet Transform , 2009, 2009 Second International Conference on Intelligent Computation Technology and Automation.

[14]  Xianmin Ma,et al.  Coal Gangue Image Process Approaches with Wavelet Analysis , 2008, 2008 Congress on Image and Signal Processing.

[15]  Debi Prasad Tripathy,et al.  Novel Methods for Separation of Gangue from Limestone and Coal using Multispectral and Joint Color-Texture Features , 2017 .

[16]  Qian Mu,et al.  The Application of Coal Cleaning Detection System Based on Embedded Real-Time Image Processing , 2013, 2013 Fifth International Conference on Measuring Technology and Mechatronics Automation.

[17]  Zhixin Lv,et al.  Differentiation between Coal and Stone through Image Analysis of Texture Features , 2007, 2007 IEEE International Workshop on Imaging Systems and Techniques.

[18]  Xian-Min Ma,et al.  Application of Rough Set Theory in Coal Gangue Image Process , 2009, 2009 Fifth International Conference on Information Assurance and Security.

[19]  Yin Zhong,et al.  Identification of Coal and Gangue by Self-Organizing Competitive Neural Network and SVM , 2010, 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics.

[20]  Xian-Min Ma,et al.  A Revised Edge Detection Algorithm Based on Wavelet Transform for Coal Gangue Image , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[21]  Lixin Li,et al.  The thermal activation process of coal gangue selected from Zhungeer in China , 2016, Journal of Thermal Analysis and Calorimetry.

[22]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[23]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[24]  B. Wang,et al.  Carbon emissions accounting for China’s coal mining sector: invisible sources of climate change , 2018, Natural Hazards.

[25]  Chang Liu,et al.  Coal–Rock Interface Recognition Based on Permutation Entropy of LMD and Supervised Kohonen Neural Network , 2019, Current Science.

[26]  Chen Bo,et al.  Notice of RetractionResearch on identification of coal and waste rock based on PCA and GA-ANN , 2010, 2010 3rd International Conference on Computer Science and Information Technology.