Transactions on Mass-Data Analysis of Images and Signals P-ISSN1868-6451, E-ISSN 2509-9353, ISBN 978-3-942952-88-0
Volume 12 - Number 1 - September 2021 - Page 13-21
Detection of Hygiene-Relevant Parameters from Cereal Grains such as Mycotoxin based on Microscopic Imaging, Intelligent Image Processing and Data Mining
Petra Perner
Institute of Computer Vision and Applied Computer Sciences, IBaI, Germany
Abstract
We present our work on a novel method for the detection of hygiene-relevant parameters from grains of cereal crops based on microscopic image acquisition, im age processing, and interpretation methods as well as data mining method. Hygiene-relevant parameters are for example Mycotoxins. We describe the data acquisition, the 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. We compare the results to the conventional findings with DON-values determination obtained by Elisa tests. The results show that with imaging methods and the new computer science methods it is possible to develop new measurement method and to produce new insights into the quality control of food stuff.
Keywords: Grain Hygiene-Relevant Parameters, Grain Product Quality, Mycotoxin Detection, Microscopic Image Analysis, Image Interpretation, Data Mining
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