Image processing algorithms in the assessment of grain damage degree

IF 1.2 Q3 Computer Science Bio-Algorithms and Med-Systems Pub Date : 2021-10-12 DOI:10.1515/bams-2021-0063
Wojciech Maliga, W. Dudziński, M. Łabowska, J. Detyna, Marcin Łopusiewicz, H. Bujak
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引用次数: 1

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.
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图像处理算法在晶粒损伤程度评估中的应用
摘要目的对谷物损伤程度图像处理算法的评价进行了初步研究。这项工作的目的是开发一种工具,可以分析黑麦细菌的样本横截面。方法在一定深度下,以等时间间隔拍摄的一系列照片为基础,对颗粒截面进行分析。横截面将用于创建额外的虚拟横截面,允许分析整个样本量。最终的计划是产生两个互相垂直的横截面。基于从样本截面读取的体积数据,将生成物体的三维模型。结果通过对模型表面的分析,可以发现可能存在的颗粒损伤。所开发的制备研究材料的方法和专有应用允许识别生物材料(谷物)的内部缺陷。结论本方法在农业食品行业具有一定的应用价值。然而,还有很多研究要做。这些工作的主要目的应该是显著减少单个阶段的耗时性质,以及提高重建图像的质量。
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来源期刊
Bio-Algorithms and Med-Systems
Bio-Algorithms and Med-Systems MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
3
期刊介绍: The journal Bio-Algorithms and Med-Systems (BAMS), edited by the Jagiellonian University Medical College, provides a forum for the exchange of information in the interdisciplinary fields of computational methods applied in medicine, presenting new algorithms and databases that allows the progress in collaborations between medicine, informatics, physics, and biochemistry. Projects linking specialists representing these disciplines are welcome to be published in this Journal. Articles in BAMS are published in English. Topics Bioinformatics Systems biology Telemedicine E-Learning in Medicine Patient''s electronic record Image processing Medical databases.
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