Kapitel/Beitrag aus dem Buch: Längle, T et al. 2017. OCM 2017 – 3rd International Conference on Optical Characterization of Materials, March 22nd – 23rd, 2017, Karlsruhe, Germany : Conference Proceedings.
Sensor-based sorting provides state-of-the-art solutions for sorting of cohesive, granular materials. Systems are tailored to a task at hand, for instance by means of sensors and implementation of data analysis. Conventional systems utilize scanning sensors which do not allow for extraction of motionrelated information of objects contained in a material feed. Recently, usage of area-scan cameras to overcome this disadvantage has been proposed. Multitarget tracking can then be used in order to accurately estimate the point in time and position at which any object will reach the separation stage. In this paper, utilizing motion information of objects which can be retrieved from multitarget tracking for the purpose of classification is proposed. Results show that corresponding features can significantly increase classification performance and eventually decrease the detection error of a sorting system.
Maier, G et al. 2017. Improving material characterization in sensor-based sorting by utilizing motion information. In: Längle, T et al (eds.), OCM 2017 – 3rd International Conference on Optical Characterization of Materials, March 22nd – 23rd, 2017, Karlsruhe, Germany : Conference Proceedings. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.58895/ksp/1000063696-11
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Veröffentlicht am 24. März 2017