Pellet represent a well spread commodity for energy production in Europe with a rapidly increasing market. Previous studies evidenced as the color could be used for visual prediction of pellets quality through RGB calibration methodologies paired with image analysis techniques. The open source software and hardware available nowadays represent a great possibility for prototypes development due to their affordable nature and commercially suitable license. Therefore, this work point to the development of an image analysis based open source conveyor belt prototype for pellet quality assessment. The realized open source system, coupled with image analysis, could allow a rapid characterization of wood pellet and chip. Moreover, being based on open source technologies, it resulted to be low cost and could be able to characterize large quantities of products. The system, following a proper calibration, may be used in future for products quality labelling and certifications.

Image analysis based open source conveyor belt prototype for wood pellet and chip quality assessment

PROTO, Andrea Rosario;
2016-01-01

Abstract

Pellet represent a well spread commodity for energy production in Europe with a rapidly increasing market. Previous studies evidenced as the color could be used for visual prediction of pellets quality through RGB calibration methodologies paired with image analysis techniques. The open source software and hardware available nowadays represent a great possibility for prototypes development due to their affordable nature and commercially suitable license. Therefore, this work point to the development of an image analysis based open source conveyor belt prototype for pellet quality assessment. The realized open source system, coupled with image analysis, could allow a rapid characterization of wood pellet and chip. Moreover, being based on open source technologies, it resulted to be low cost and could be able to characterize large quantities of products. The system, following a proper calibration, may be used in future for products quality labelling and certifications.
2016
pellet; Image analysis; Wood
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/3037
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