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https://doi.org/10.21256/zhaw-27307| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics |
| Autor/-in: | Matuttis, Hans-Georg Holler, Silvia Casiraghi, Federica Schneider, Johannes Josef Faggian, Alessia Füchslin, Rudolf Marcel Hanczyc, Martin Michael |
| et. al: | No |
| DOI: | 10.1007/978-3-031-23929-8_5 10.21256/zhaw-27307 |
| Tagungsband: | Artificial Life and Evolutionary Computation |
| Seite(n): | 51 |
| Seiten bis: | 62 |
| Angaben zur Konferenz: | XV Italian Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021 |
| Erscheinungsdatum: | 22-Jan-2023 |
| Reihe: | Communications in Computer and Information Science |
| Reihenzählung: | 1722 |
| Verlag / Hrsg. Institution: | Springer |
| Verlag / Hrsg. Institution: | Cham |
| ISBN: | 978-3-031-23928-1 978-3-031-23929-8 |
| Sprache: | Englisch |
| Schlagwörter: | Image processing; Hough transform; Cluster of droplets in fluids |
| Fachgebiet (DDC): | 540: Chemie |
| Zusammenfassung: | We explain how to optimize the image analysis of mixed clusters of red and green droplets in solvents with various degrees of sharpness, brightness, contrast and density. The circular Hough Transform is highly efficient for separated circles with reasonable background contrast, but not for large amounts of partially overlapping shapes, some of them blurred, as in the images of our dense droplet suspensions. We explain why standard approaches for image improvement fail and present a “shootout” approach, where already detected circles are masked, so that the removal of sharp outlines improves the relative optical quality of the remaining droplets. Nevertheless, for intrinsic reasons, there are limits to the accuracy of data which can be obtained on very dense clusters. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/27307 |
| Volltext Version: | Akzeptierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Angewandte Mathematik und Physik (IAMP) |
| Publiziert im Rahmen des ZHAW-Projekts: | ACDC – Artificial Cells with Distributed Cores to Decipher Protein Function |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2023_Matuttis-etal_Droplet-recognition-shootout-heuristics_WIVACE.pdf | Accepted Version | 11.54 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Matuttis, H.-G., Holler, S., Casiraghi, F., Schneider, J. J., Faggian, A., Füchslin, R. M., & Hanczyc, M. M. (2023). The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics [Conference paper]. Artificial Life and Evolutionary Computation, 51–62. https://doi.org/10.1007/978-3-031-23929-8_5
Matuttis, H.-G. et al. (2023) ‘The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics’, in Artificial Life and Evolutionary Computation. Cham: Springer, pp. 51–62. Available at: https://doi.org/10.1007/978-3-031-23929-8_5.
H.-G. Matuttis et al., “The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics,” in Artificial Life and Evolutionary Computation, Jan. 2023, pp. 51–62. doi: 10.1007/978-3-031-23929-8_5.
MATUTTIS, Hans-Georg, Silvia HOLLER, Federica CASIRAGHI, Johannes Josef SCHNEIDER, Alessia FAGGIAN, Rudolf Marcel FÜCHSLIN und Martin Michael HANCZYC, 2023. The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics. In: Artificial Life and Evolutionary Computation. Conference paper. Cham: Springer. 22 Januar 2023. S. 51–62. ISBN 978-3-031-23928-1
Matuttis, Hans-Georg, Silvia Holler, Federica Casiraghi, Johannes Josef Schneider, Alessia Faggian, Rudolf Marcel Füchslin, and Martin Michael Hanczyc. 2023. “The Good, the Bad and the Ugly : Droplet Recognition by a “Shootout”-Heuristics.” Conference paper. In Artificial Life and Evolutionary Computation, 51–62. Cham: Springer. https://doi.org/10.1007/978-3-031-23929-8_5.
Matuttis, Hans-Georg, et al. “The Good, the Bad and the Ugly : Droplet Recognition by a “Shootout”-Heuristics.” Artificial Life and Evolutionary Computation, Springer, 2023, pp. 51–62, https://doi.org/10.1007/978-3-031-23929-8_5.
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