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Research Article

Recognition of coal and gangue based on multi-dimensional gray gradient feature fusion

ORCID Icon, , &
Pages 8060-8076 | Received 05 May 2022, Accepted 08 Aug 2022, Published online: 06 Sep 2022

References

  • Amandeep, S., G. Gurjot, and H. Mustapha. 2021. Robust and effective image preprocessing conglomerate method for denoising of both grayscale and color images. Journal of Electronic Imaging 31 (4):041203. doi:10.1117/1.JEI.31.4.041203.
  • An, Z. Y., X. M. Wang, B. Li, Z. L. Xiang, and B. Zhang. 2022. Robust visual tracking for UAVs with dynamic feature weight selection. Applied Intelligence. doi:10.1007/s10489-022-03719-6.
  • Chen, T. Q., and C. Guestrin. 2016. Xgboost: A scalable tree boosting system. The 22nd ACM SIGKDD International Conference. ACM, 785–94. doi:10.1145/2939672.2939785.
  • Chen, J. X., and X. K. Ran. 2019. Deep learning with edge computing: A review. Proceedings of the IEEE 107 (8):1655–74. doi:10.1109/JPROC.2019.2921977.
  • Chen, S., C. D. Wu, D. Y. Chen, and W. J. Tan. 2009. Scene classification based on gray level-gradient co-occurrence matrix in the neighborhood of interest points. IEEE, 482–85. doi:10.1109/ICICISYS.2009.5357627.
  • Deng, X. S., M. Li, S. B. Deng, and L. Wang. 2022. Hybrid gene selection approach using XGBoost and multi-objective genetic algorithm for cancer classification. Medical & Biological Engineering & Computing 60 (3):663–81. doi:10.1007/s11517-021-02476-x.
  • Dou, D. Y., W. Z. Wu, J. G. Yang, and Y. Zhuang. 2019. Classification of coal and gangue under multiple surface conditions via machine vision and relief-SVM. Powder Technology 356:1024–28. doi:10.1016/j.powtec.2019.09.007.
  • He, L., S. Wang, Y. C. Guo, K. Hu, G. Cheng, and X. Q. Wang. 2022. Study of raw coal identification method by dual-energy x- ray and dual-view visible light imaging. International Journal of Coal Preparation and Utilization 1–16. doi:10.1080/19392699.2022.2051013.
  • Hong, J. G. 1984. Gray level-gradient cooccurrence matrix texture analysis method. Acta Automatica Sinica 10 (1):22–25. (in Chinese with English abstract).
  • Jiang, J. H., Y. F. Han, H. J. Zhao, J. L. Suo, and Q. B. Cao. 2021. Recognition and sorting of coal and gangue based on image process and multilayer perceptron. International Journal of Coal Preparation and Utilization, 1–19. doi:10.1080/19392699.2021.2002852.
  • Katajamaeki, J. 2003. Methods for gamma invariant colour image processing. Image & Vision Computing 21 (6):527–42. doi:10.1016/S0262-8856(03)00033-7.
  • Kuang, Q. 2021. Image pattern recognition algorithm based on improved genetic algorithm. Journal of Physics: Conference Series 1852 (3):032038. doi:10.1088/1742-6596/1852/3/032038.
  • Li, M., Y. Duan, X. L. He, and M. L. Yang. 2022. Image positioning and identification method and system for coal and gangue sorting robot. International Journal of Coal Preparation and Utilization 42 (6):1759–77. doi:10.1080/19392699.2020.1760855.
  • Li, X., Y. L. Ma, Q. Z. Zhang, and Y. Y. Gao. 2021. EEG characteristics extraction and classification based on R-CSP and PSO-SVM. The 10th International Conference on Computer Engineering and Networks 1274:1658–67. doi:10.1007/978-981-15-8462-6_189.
  • Li, J. Y., and J. M. Wang. 2019. Comprehensive utilization and environmental risks of coal and gangue: A review. Journal of Cleaner Production 239:117946. doi:10.1016/j.jclepro.2019.117946.
  • Li, X. Y., H. M. Zhao, L. Yu, H. Y. Chen, W. Q. Deng, and W. Deng. 2022. Feature extraction using parameterized multisynchrosqueezing transform. IEEE Sensors Journal 22 (14):14263–72. doi:10.1109/JSEN.2022.3179165.
  • Liu, Y., Z. L. Zhang, X. Liu, L. Wang, and X. H. Xia. 2021. Deep learning-based image classification for online multi-coal and multi-class sorting. Computers & Geosciences 157:104922. doi:10.1016/j.cageo.2021.104922.
  • Lv, Z. Q., W. D. Wang, Z. Q. Xu, K. H. Zhang, and H. M. Lv. 2021. Cascade network for detection of coal and gangue in the production context. Powder Technology 377:361–71. doi:10.1016/j.powtec.2020.08.088.
  • Medabalimi, R., R. Bodireddy, K. Ramana, P. Kottapalli, and S. Saurabh. 2021. Texture classification using minkowski distance measure-based clustering for feature selection. Journal of Electronic Imaging 31 (4):041204. doi:10.1117/1.JEI.31.4.041204.
  • Robben, C., P. Condori, A. Pinto, R. Machaca, and A. Takala. 2020. X-Ray-Transmission based ore sorting at the san rafael tin mine. Minerals Engineering 145:105870. doi:10.1016/j.mineng.2019.105870.
  • Smith, M. L., L. N. Smith, and M. F. Hansen. 2021. The quiet revolution in machine vision-a state-of-the-art survey paper, including historical review, perspectives, and future directions. Computers in Industry 130:103472. doi:10.1016/j.compind.2021.103472.
  • Sun, Z. Y., L. L. Huang, and R. Q. Jia. 2021. Coal and gangue separating robot system based on computer vision. Sensors 21 (4):1349. doi:10.3390/s21041349.
  • Tajeripour, F., M. Saberi, M. Rezaei, and S. F. Ershad. 2011. Texture classification approach based on combination of random threshold vector technique and co-occurrence matrixes. International Conference on Computer Science & Network Technology. IEEE 4:2303–06. doi:10.1109/ICCSNT.2011.6182434.
  • Tripathy, D. P., and K. Reddy. 2017. Novel methods for separation of gangue from limestone and coal using multispectral and joint color-texture features. Journal of the Institution of Engineers (India): Series D 98 (1):109–17. doi:10.1007/s40033-015-0106-4.
  • Wang, G. 2020. Design and implementation of english text recognition system under robot vision. Journal of Physics: Conference Series 1621 (1):012049. doi:10.1088/1742-6596/1621/1/012049.
  • Wang, C. L., Z. R. Li, N. Dey, Z. C. Li, A. S. Ashour, S. J. Fong, R. S. Sherratt, L. J. Wu, and F. Q. Shi. 2018. Histogram of oriented gradient based plantar pressure image feature extraction and classification employing fuzzy support vector machine. Journal of Medical Imaging & Health Informatics 8 (4):842–54. doi:10.1166/jmihi.2018.2310.
  • Wang, P., F. L. Liu, C. F. Yang, and X. Y. Luo. 2018. Parameter estimation of image gamma transformation based on zero-value histogram bin locations. Signal Processing Image Communication 64:33–45. doi:10.1016/j.image.2018.02.011.
  • Wu, D. Q., and C. X. Wu. 2022. Research on the time-dependent split delivery green vehicle routing problem for fresh agricultural products with multiple time windows. Agriculture 12 (6):739. doi:10.3390/agriculture12060793.
  • Xia, W. C., G. Y. Xie, and Y. L. Peng. 2015. Recent advances in beneficiation for low rank coals. Powder Technology 277:206–21. doi:10.1016/j.powtec.2015.03.003.
  • Zhai, A. B., X. B. Wen, and X. Zhang. 2017. Retrieval algorithm for texture image based on improved dual tree complex wavelet transform and gray gradient co-occurrence matrix. Computer Science 44 (06):274–77. doi:10.11896/j.issn.1002-137X.2017.06.048.
  • Zhang, Z. L., Y. Liu, Q. Hu, Z. W. Zhang, L. Wang, X. Liu, and H. Y. Xia. 2020. Multi-Information online detection of coal quality based on machine vision. Powder Technology 374:250–62. doi:10.1016/j.powtec.2020.07.040.
  • Zhang, Y. H., and L. J. Yan. 2022. A fast face recognition based on image gradient compensation for feature description. Multimedia Tools and Applications 81(18): 26015–34. doi:10.1007/s11042-022-12804-4.
  • Zhang, Y., H. Z. Zhu, J. B. Zhu, Z. B. Ou, T. Shen, J. J. Sun, and A. A. Feng. 2021. Experimental study on separation of lumpish coal and gangue using X-ray. Energy Sources Part a Recovery Utilization & Environmental Effects. doi:10.1080/15567036.2021.1976325.
  • Zhao, Y., Q. L. Han, and Y. D. Zhao. 2018. Improved FCM method for pore identification based on grayscale gradient features. Transactions of the Chinese Society for Agricultural Machinery 49(3):279–86. in Chinese with English abstract. doi:10.6041/j.issn.1000-1298.2018.03.033.
  • Zhao, R. Q., H. Q. Wang, K. Wang, Z. Wang, and W. T. Liu. 2020. Recognition of bronze inscriptions image based on mixed features of histogram of oriented gradient and gray level co-occurrence matrix. Laser & Optoelectronics Progress 57 (12):98–104. in Chinese with English abstract. doi:10.3788/LOP57.121003.
  • Zhao, Y. M., X. L. Yang, Z. F. Luo, C. L. Duan, and S. L. Song. 2014. Progress in developments of dry coal beneficiation. International Journal of Coal Science & Technology 1 (1):103–12. doi:10.1007/s40789-014-0014-5.
  • Zhou, X. B., H. J. Ma, J. G. Gu, H. L. Chen, and W. Deng. 2022. Parameter adaptation-based ant colony optimization with dynamic hybrid mechanism. Engineering Applications of Artificial Intelligence 114:105139. doi:10.1016/j.engappai.2022.105139.

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