Separating nut-shell pieces from hazelnuts and pistachio kernels using impact vibration analysis

Signal Processing and Communications Applications Conference(2013)

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Abstract
In this article nut-shell pieces are separated from pistachio kernels and hazelnut kernels using impact vibration analysis. Vibration signals are recorded and analyzed in real-time. Mel-kepstral feature parameters and line spectral frequency values are extracted from the vibration signals. Feature parameters are classified using a Support Vector Machine (SVM) which was trained a priori using a manually classified data set. An average classification rate of 96.% and 98.3%was achieved with Antep-style Turkish pistachio nuts and hazelnuts. An important feature of the method is that it is easily trainable for other kinds of pistachio nuts and other nuts including walnuts.
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Key words
food products,food technology,impact (mechanical),production engineering computing,separation,signal processing,support vector machines,vibrations,Mel-kepstral feature parameters,SVM,feature parameters,hazelnut kernels,impact vibration analysis,line spectral frequency values,nut-shell pieces separation,pistachio kernels,support vector machine,vibration signals,walnuts,impact vibration analysis,line spectral frequencies,mel-kepstral feature
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