Detection of empty hazelnuts from fully developed nuts by impact acoustics
Author
Onaran, İbrahim
Dülek, Berkan
Pearson, T. C.
Yardımcı, Y.
Çetin, A. Enis
Date
2005Source Title
Proceedings of the 13th European Signal Processing Conference, EUSIPCO 2005
Publisher
IEEE
Language
English
Type
Conference PaperItem Usage Stats
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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 signalsComputing 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