Automatic quality control of cereals in particular wheat-subtask detection of hygiene-relevant parameters

  • Authors:

  • Petra Perner;Thomas Günther

  • Affiliations:

  • Institute of Computer Vision and Applied Computer Sciences, Leipzig;JenaBios GmbH, Jena

  • Venue:
  • MDA'06/07 Proceedings of the 2007 international conference on Advances in mass data analysis of signals and images in medicine biotechnology and chemistry
  • Year:
  • 2007

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Abstract

We are going on to develop a novel method for the detection of hygiene-relevant parameters from grains of cereal crops based on intelligent image acquisition and interpretation methods as well as data mining methods. The work presented here is part of a larger project aiming to develop an automatic system to the determination of the quality of cereals in particular wheat. We present our first results that describe the data acquisition, the planned image analysis and interpretation method as well as the reasoning methods that can map the automatic acquired parameters of grain to the relevant hygiene parameters. The preliminary results show that with the new computer science methods it is possible to come up with new insights into the quality control of food stuff.