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  4. Improving material characterization in sensor-based sorting by utilizing motion information
 
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2017
Conference Paper
Title

Improving material characterization in sensor-based sorting by utilizing motion information

Abstract
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 motion related 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.
Author(s)
Maier, Georg  
Pfaff, F.
Becker, F.
Pieper, C.
Gruna, Robin  
Noack, B.
Kruggel-Emden, H.
Längle, Thomas  
Hanebeck, U.D.
Wirtz, S.
Scherer, V.
Beyerer, Jürgen  
Mainwork
OCM 2017, 3rd International Conference on Optical Characterization of Materials  
Conference
International Conference on Optical Characterization of Materials (OCM) 2017  
File(s)
Download (7.34 MB)
Rights
Use according to copyright law
DOI
10.24406/publica-fhg-395775
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Keyword(s)
  • optical inspection

  • sensor-based sorting

  • multitarget tracking

  • classification

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