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Method for pests detecting in stored grain based on spectral residual saliency edge detection

             

摘要

cqvip:Pests detecting is an important research subject in grain storage field.In the past decades,many edge detection methods have been applied to the edge detection of stored grain pests.Although some of them can realize the stored grain pests detecting,precision and robustness are not good enough.Spectral residual(SR)saliency edge detection defines the logarithmic spectrumof image as novelty part of the image information.The remaining spectrumis converted to the airspace to obtain edge detection results.SR algorithm is completely based on frequency domain processing.It not only can effectively simplify the target detection algorithm,but also can improve the effectiveness of target recognition.The experimental results show that the edge results of stored grain pests detected by SR method are effective and stable.

著录项

  • 来源
    《粮油科技:英文版 》 |2019年第2期|P.33-38|共6页
  • 作者单位

    College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China;

    Key Laboratory of Grain Information Processing and Control Henan University of Technology Ministry of Education Zhengzhou 450001 China;

    Henan Academy of Science Applied Physics Institute Co. Ltd Zhengzhou 450001 China;

    Luoyang Institute of Science and Technology Department of Computer and Information Engineering Luoyang 471000 China;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 TN9;
  • 关键词

    Stored grain pests; Saliency detection; Spectral residual (SR); Edge detection;

    机译:储存的谷物害虫;显着性检测;频谱残差(SR);边缘检测;
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