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Motion-based material characterization in sensor-based sorting
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DOI：10.1515/teme-2017-0063.png)
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Abstract
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Abstract
Sensor-based sorting provides state-of-the-art solutions for sorting cohesive, granular materials. Typically, involved
sensors, illumination, implementation of data analysis and other components are designed and chosen according to the
sorting task at hand. A common property of conventional systems is the utilization of scanning sensors. However, the
usage of area-scan cameras has recently been proposed. When observing objects at multiple time points, the corresponding
paths can be reconstructed by using multiobject tracking. This in turn allows to accurately estimate the point in time
and position at which any object will reach the separation stage of the optical sorter and hence contributes to decreasing
the error in physical separation. In this paper, it is proposed to further exploit motion information for the purpose of
material characterization. By deriving suitable features from the motion information, we show that high classification
performance is obtained for an exemplary classification task. The approach therefore contributes towards decreasing the
detection error of sorting systems.
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