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Blue Apple – an algorithm to realize agricultural classification under difficult light and color situations

  • Computer-image processing becomes more and more important in the analysis of data in biological and agricultural research and practice. However, robust image processing is highly de pendent on the histogram analysis algorithms used and the quality of the data being processed. The algorithm presented here aims to improve the accuracy of the classification of image data generated under complex boundary situations and inconsistent lighting conditions. Using the example of the determination of nitrogen content of tomato leaves and the qualitative determination of starch con tent of apples on the basis of color image processing, we showed that the developed algorithm is able to perform a robust classification and represents an improvement to simple histogram analysis.

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Metadaten
Author:Jonas Credner, Peter Rehrmann, Waldemar Raaz, Thomas Rath
Title (English):Blue Apple – an algorithm to realize agricultural classification under difficult light and color situations
URL:https://dl.gi.de/server/api/core/bitstreams/bfcca521-856f-4604-ba93-05cd7ed7a6eb/content
ISBN:978-3-88579-724-1
Parent Title (English):Informatik in der Land-, Forst- und Ernährungswirtschaft Fokus: Resiliente Agri-Food-Systeme
Document Type:Conference Proceeding
Language:English
Year of Completion:2023
Release Date:2024/03/22
Tag:N-analysis plants; classification; color image processing; histogram analysis; starch detection apples
Page Number:12
First Page:53
Last Page:65
Note:
43. GIL-Jahrestagung 13.-14. Februar 2023 Osnabrück, Germany
Faculties:Fakultät AuL
DDC classes:500 Naturwissenschaften und Mathematik / 500 Naturwissenschaften
Review Status:Veröffentlichte Fassung/Verlagsversion