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.
Author: | Jonas Credner, Peter Rehrmann, Waldemar Raaz, Thomas Rath |
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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 |