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Research on the Application of Markov Random Field in Paper Disease Detection
  
DOI：10.11980/j.issn.0254-508X.2019.05.009
Key Words:paper disease image  MarKov random field  texture feature parameter  maximum difference
Author NameAffiliation
LEI Yangbo College of Mechanical and Electrical Engineering， Shaanxi University of Science and Technology， Xi’an， Shaanxi Province， 710021 
HUANG Xun* College of Mechanical and Electrical Engineering， Shaanxi University of Science and Technology， Xi’an， Shaanxi Province， 710021 
WANG Yangyang College of Mechanical and Electrical Engineering， Shaanxi University of Science and Technology， Xi’an， Shaanxi Province， 710021 
CHEN Hao College of Mechanical and Electrical Engineering， Shaanxi University of Science and Technology， Xi’an， Shaanxi Province， 710021 
HUANG Lun College of Mechanical and Electrical Engineering， Shaanxi University of Science and Technology， Xi’an， Shaanxi Province， 710021 
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Abstract:Paper disease detection is an important part of paper production process.Image segmentation is a necessary step in paper disease detection.In order to solve the problems of error segmentation and over-segmentation in threshold segmentation and edge detection segmentation， this paper proposed disease image segmentation method based on MarKov random field.The texture feature parameters were obtained by using MarKov random field theory to analyze the paper disease image texture.The normal background and the paper disease region were segmented using the texture feature parameters and the maximum difference.Experiment results showed that compared with other segmentation algorithms， the Markov random field paper image segmentation method effectively extracted the texture details and contour features of the paper disease image， and improvd the segmentation accuracy.
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