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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Wheat and hazelnut inspection with impact acoustics time-frequency patterns

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      Author
      İnce, N. F.
      Onaran, İbrahim
      Tewfik, A. H.
      Kalkan, H.
      Pearson, T.
      Çetin, A. Enis
      Yardimci, Y.
      Date
      2007-06
      Source Title
      2007 ASABE Annual International Meeting, Technical Papers
      Publisher
      ASABE
      Pages
      [1] - [9]
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
      103
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      53
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      Abstract
      Kernel damage caused by insects and fungi is one of the most common reason for poor flour quality. Cracked hazelnut shells are prone to infection by cancer producing mold. We propose a new adaptive time-frequency classification procedure for detecting cracked hazelnut shells and damaged wheat kernels using impact acoustic emissions recorded by dropping wheat kernels or hazelnut shells on a steel plate. The proposed algorithm is based on a flexible local discriminant bases (F-LDB) procedure. The F-LDB method combines local cosine packet analysis and a frequency axis clustering approach which supports individual time and frequency band adaptation. Discriminant features are extracted from the adaptively segmented acoustic signal, sorted according to a Fisher class separability criterion, post processed by principal component analysis and fed to linear discriminant. We describe experimental results that establish the superior performance of the proposed approach when compared with prior techniques reported in the literature or used in the field. Our approach achieved classification accuracy in paired separation of undamaged wheat kernels from IDK, Pupae and Scab damaged kernels with 96%, 82% and 94%. For hazelnuts the accuracy was 97.1%.
      Keywords
      Acoustic measurement
      Adaptive signal processing
      Pattern classification
      Time-frequency analysis
      Acoustic emissions
      Algorithms
      Pattern recognition
      Principal component analysis
      Signal processing
      Cracked hazelnut
      Kernel damage
      Crops
      Permalink
      http://hdl.handle.net/11693/27084
      Published Version (Please cite this version)
      https://doi.org/10.13031/2013.23455
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      • Department of Electrical and Electronics Engineering 3524
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