Laser & Optoelectronics Progress, Volume. 55, Issue 12, 121504(2018)

Smoke Classification in Copper Smelting Process Based on Discrete Cosine Transform Features and Hidden Markov Model

Hongwei Zhang1,3、*, Lingjie Zhang1, Xiaofeng Yuan2, and Zhihuan Song3
Author Affiliations
  • 1 College of Electronics and Information, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
  • 2 School of Information Science and Engineering, Central South University, Changsha, Hunan 410083, China
  • 3 Department of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
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    References(23)

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    [16] Mredhula L, Dorairangaswamy M A. Image denoising using principal component analysis (PCA) and pixel surge model (PSM)[J]. International Journal of Signal and Imaging Systems Engineering, 9, 311-319(2016).

    [17] Naidu V P S, Raol J R. Pixel-level image fusion using wavelets and principal component analysis[J]. Defence Science Journal, 58, 338-352(2008).

    [18] Hanbay K, Talu M F, Ozguven O F. Real time fabric defect detection by using Fourier transform[J]. Journal of the Faculty of Engineering and Architecture of Gazi University, 32, 151-158(2017).

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    Hongwei Zhang, Lingjie Zhang, Xiaofeng Yuan, Zhihuan Song. Smoke Classification in Copper Smelting Process Based on Discrete Cosine Transform Features and Hidden Markov Model[J]. Laser & Optoelectronics Progress, 2018, 55(12): 121504

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    Paper Information

    Category: Machine Vision

    Received: Apr. 20, 2018

    Accepted: Jul. 12, 2018

    Published Online: Aug. 1, 2019

    The Author Email: Hongwei Zhang (zhanghongwei@zju.edu.cn)

    DOI:10.3788/LOP55.121504

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