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Tytuł artykułu

On the role of image processing techniques in the quantitative image analysis

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article explores how qualitative image analysis impacts the process of image interpretation, particularly in composite microstructure analysis. It highlights the importance of high-quality images for accurate computer-based object detection, emphasizing the limitations of rigid pixel-based rules compared to human visual perception. The study underscores the need for optimal imaging conditions to avoid image defects that hinder precise computational analyses in scientific and industrial applications
Wydawca
Rocznik
Strony
311--317
Opis fizyczny
Bibliogr. 18 poz., rys.
Twórcy
  • Cracow University of Technology, Faculty of Mechanical Engineering, Krakow
Bibliografia
  • 1. Franta A., Zając D., 2022. Carbon fiber reinforced polymer and tensegrity structures in search of model architectural and engineering solutions, Technical Transactions, 119, art. e2022013. DOI: 10.37705/TechTrans/e2022013
  • 2. Gadek, A., Kuciel, S., Wojnar, L., Dziadur, W., 2006. Application of computer-aided analysis of an image for assessment of reinforced polymers structures. Polimery 51, 206-211, DOI: 10.14314/polimery.2006.206
  • 3. Kurzydłowski, K.J., Ralph , B., 1995. The Quantitative description of the microstructure of materials. CRC Press, Boca Ration, CRC Press, Boca Ration.
  • 4. Opydo, M., Dudek, A., Kobyłecki, R., 2019. Characteristics of solids accumulation on steel samples during co-combustion of biomass and coal in a CFB boiler, Biomass and Bioenergy, 120, 291-300. DOI: 10.1016/j.biombioe.2018.11.027
  • 5. Otsu, N., 1979. A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics 9, 62-66. DOI: 10.1109/TSMC.1979.4310076
  • 6. Pietraszek, J., Radek, N., Goroshko, A.V., 2020. Challenges for the DOE methodology related to the introduction of Industry 4.0, Production Engineering Archives, 26(4), 190-194. DOI: 10.30657/pea.2020.26.33
  • 7. Radek, M., Pietraszek, A., Kozień, A., Radek, K., Pietraszek, J., 2023. Matching Computational Tools to User Competence Levels in Education of Engineering Data Processing, Materials Research Proceedings, 34, 453-459. DOI: 10.21741/9781644902691-52
  • 8. Radek, N., 2009. Determining the operational properties of steel beaters after electrospark deposition, Eksploatacja i Niezawodnosc, 44(4), 10-16..
  • 9. Radek, N., Antoszewski, B., 2009. The influence of laser treatment on the properties of electro-spark deposited coatings, Kovove Materialy, 47(1), 31-38.
  • 10. Radek, N., Pietraszek, J., Szczotok, A., Fabian, P., Kalinowski, A., 2020. Microstructure and tribological properties of DLC coatings, Materials Research Proceedings, 17, 171-176. DOI: 10.21741/9781644901038-26
  • 11. Radek, N., Wajs, E., Luchka, M., 2008. The WC-Co electrospark alloying coatings modified by laser treatment, Powder Metallurgy and Metal Ceramics, 47(3-4), 197-201. DOI: 10.1007/s11106-008-9005-7
  • 12. Russ, J.C., DeHoff, R.T., 2000. Practical stereology. Kluwer Academic/Plenum Publisher.
  • 13. Siwiec, D., Dwornicka, R., Pacana, A., 2020. Improving the non-destructive test by initiating the quality management techniques on an example of the turbine nozzle outlet, Materials Research Proceedings, 17, 16-22. DOI: 10.21741/9781644901038-3
  • 14. Szczotok A., 2023. Assessment of the feasibility of determining the volume fraction and characteristics of the size, shape and distribution of γ’ phase precipitates in nickel-based superalloys, Technical Transactions, 120, art. e2023011. DOI: 10.37705/TechTrans/e2023011
  • 15. Szeliski, R., 2022. Computer Vision. Algorithms and Application. Springer International Publishing, Heidelberg.
  • 16. Szewczyk-Nykiel A., 2023. The influence of carbide reinforcement on the properties of sintered aluminium alloy matrix composites, Technical Transactions, 120, art. e2023005. DOI: 10.37705/TechTrans/e2023005
  • 17. Ulewicz, R., 2018. Outsorcing quality control in the automotive industry, MATEC Web of Conf., 183, art.03001. DOI: 10.1051/matecconf/201818303001
  • 18. Ulewicz, R., Mazur, M., Knop, K., Dwornicka, R., 2020. Logistic controlling processes and quality issues in a cast iron foundry, Materials Research Proceedings, 17, 65-71. DOI: 10.21741/9781644901038-10
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-10c20c0e-b457-478b-b6bf-fd9179078c45
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