Image processing algorithms in the assessment of grain damage degree

Author:

Maliga Wojciech1,Dudziński Włodzimierz1,Łabowska Magdalena2,Detyna Jerzy2ORCID,Łopusiewicz Marcin2,Bujak Henryk34

Affiliation:

1. Department of Materials Science, Welding and Strength of Materials , Wrocław University of Science and Technology , Wrocław , Poland

2. Department of Mechanics, Materials and Biomedical Engineering , Wrocław University of Science and Technology , Wrocław , Poland

3. Department of Genetics, Plant Breeding and Seed Production , Wrocław University of Environmental and Life Sciences , Wrocław , Poland

4. Research Centre for Cultivar Testing , Słupia Wielka , Poland

Abstract

Abstract Objectives The paper presents preliminary results on the assessment of algorithms used in image processing of the grain damage degree. The purpose of the work is developing a tool allowing to analyse sample cross-sections of rye germs. Methods The analysis of the grain cross-sections was carried out on the basis of a series their photos taken at equal time intervals at a set depth. The cross-sections will be used to create additional virtual cross-sections allowing to analyse the whole sample volume. The ultimate plan is to generate two cross-sections perpendicular to each other. Based on volumetric data read from the sample section, a three-dimensional model of an object will be generated. Results The analysis of model surface will allowed us to detect possible grain damage. The developed method of preparing the research material and the proprietary application allowed for the identification of internal defects in the biological material (cereal grains). Conclusions The presented methodology may be used in the agri-food industry in the future. However, much research remains to be done. These works should primarily aim at significantly reducing the time-consuming nature of individual stages, as well as improving the quality of the reconstructed image.

Publisher

Walter de Gruyter GmbH

Subject

Health Informatics,Biochemistry, Genetics and Molecular Biology (miscellaneous),Medicine (miscellaneous),General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Implementation and Optimization of High-Performance Image Processing Algorithms Based on Artificial Intelligence;2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS);2023-11-24

2. Online classification of soybean seeds based on deep learning;Engineering Applications of Artificial Intelligence;2023-08

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