|Publication type:||Conference paper|
|Type of review:||Peer review (publication)|
|Title:||The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics|
Schneider, Johannes Josef
Füchslin, Rudolf Marcel
Hanczyc, Martin Michael
|Proceedings:||Artificial Life and Evolutionary Computation|
|Conference details:||XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021|
|Series:||Communications in Computer and Information Science|
|Publisher / Ed. Institution:||Springer|
|Publisher / Ed. Institution:||Cham|
|Subjects:||Image processing; Hough transform; Cluster of droplets in fluids|
|Subject (DDC):||540: Chemistry|
|Abstract:||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.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Applied Mathematics and Physics (IAMP)|
|Published as part of the ZHAW project:||ACDC – Artificial Cells with Distributed Cores to Decipher Protein Function|
|Appears in collections:||Publikationen School of Engineering|
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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, 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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