Agglomerates processing on in-flight images of granular products

Frederic Ros; S. Guillaume; Francis Sevila

doi:10.1117/12.164960

29 November 1993 Agglomerates processing on in-flight images of granular products

Frederic Ros, S. Guillaume, Francis Sevila

Proceedings Volume 2063, Vision, Sensors, and Control for Automated Manufacturing Systems; (1993) https://doi.org/10.1117/12.164960
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

Abstract

Image analysis can be used to characterize granular populations in many processes in food industry or in agricultural engineering. Either global or individual parameters can be extracted from the image. However, granular products may appear agglomerate on the image, bringing biasing on individual parameters. Combining statistical and neural network technics enables the build of a system which can recognize if products are agglomerate or not. To process images after agglomerates detection, two approaches have been studied: the first is based on erosion, followed by conditional dilation with the original image; the second takes advantage of the graph's properties of the agglomerate's skeleton.

Citation Download Citation

Frederic Ros, S. Guillaume, and Francis Sevila "Agglomerates processing on in-flight images of granular products", Proc. SPIE 2063, Vision, Sensors, and Control for Automated Manufacturing Systems, (29 November 1993); https://doi.org/10.1117/12.164960

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