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The Secondary Identification of Paper Defects Based on Adaptive Neural-fuzzy Inference System
  
DOI：10.11980/j.issn.0254-508X.2017.12.010
Key Words:machine vision  FPGA  secondary identification of paper disease  adaptive neural fuzzy inference system (ANFIS)
Fund Project:陕西省教育厅专项科技项目（16JK1105）；陕西省科技攻关项目（2016GY 005）。
Author NameAffiliation
王亚波1 1.陕西科技大学电气与信息工程学院，陕西西安，710021 
周　强1,* 1.陕西科技大学电气与信息工程学院，陕西西安，710021 
王伟刚1 1.陕西科技大学电气与信息工程学院，陕西西安，710021 
王　莹2 2.陕西科技大学材料科学与工程学院，陕西西安，710021 
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Abstract:In order to ensure the contradiction between the speed and accuracy in paper defects detection on the wide and high speed paper machine, a method of paper defects secondary identification was put forward based on adaptive neural-fuzzy inference system (ANFIS) on the mode of “FPGA+computer”. The paper images collected by CCD cameras were completed image preprocessing and the first identification through FPGA; by using the ANFIS, the computer was able to complete the second identification of the suspected paper defects area to determine whether the paper defects existed and its type. Experiments showed that the method could accurately identify various paper defects.
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