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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Detection of empty hazelnuts from fully developed nuts by impact acoustics

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      Author
      Onaran, İbrahim
      Dülek, Berkan
      Pearson, T. C.
      Yardımcı, Y.
      Çetin, A. Enis
      Date
      2005
      Source Title
      Proceedings of the 13th European Signal Processing Conference, EUSIPCO 2005
      Publisher
      IEEE
      Language
      English
      Type
      Conference Paper
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      Abstract
      Shell-kernel weight ratio is the main determinate of quality and price of hazelnuts. Empty hazelnuts and nuts containing undeveloped kernels may also contain mycotoxin producing molds, which can cause cancer. A prototype system was set up to detect empty hazelnuts by dropping them onto a steel plate and processing the acoustic signal generated when kernels impact the plate. The acoustic signal was processed by five different methods: 1) modeling of the signal in the time domain, 2) computing time domain signal variances in short time windows, 3) analysis of the frequency spectra magnitudes, 4) maximum amplitude values in short time windows, and 5) line spectral frequencies (LSFs). Support Vector Machines (SVMs) were used to select a subset of features and perform classification. 98% of fully developed kernels and 97% of empty kernels were correctly classified.
      Keywords
      Acoustic signals
      Computing time
      Frequency spectra
      Impact acoustics
      Line spectral frequencies
      Maximum amplitude
      Prototype system
      Steel plates
      Time domain
      Time windows
      Acoustic waves
      Signal detection
      Support vector machines
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      http://hdl.handle.net/11693/27334
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      • Department of Electrical and Electronics Engineering 3619
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