Background The code labels microspheres and counts them. Further, the code determines which microspheres are independent of microsphere-microsphere collisions by their relative position to the other microspheres in an image. Images were taken with a full-frame visual camera (Sony Alpha 7RII) with a long-distance-microscopy lens (K2 DistaMax). Description of the dataset image_data_all.zip contains 228 tif-format images taken in a single experiment the images show borosilicate microspheres with diameters from 63 to 75 µm during the experiment, the microspheres are detached from the substrate and are transported out of the image functions_particle_labeling.jl contains all necessary functions for particle labeling analysis_protocol.jl is an example, that first determines a color threshold, and then labels all microspheres in all images stored in "image_data_all/substrate_a/image_data_single_experiment" post_processing_visualisation.R is an r-script, that reads the output of analysis_protocol.jl and demonstrates how logistic functions were fitted to the data We used julia 1.8.5 and R 4.3.0.

{"references": ["Bezanson, J., Edelman, A., Karpinski, S., and Shah, V.B. (2017). Julia: A Fresh Approach to Numerical Computing. SIAM Rev 59 (1):65\u201398. doi:10.1137/141000671.", "R Core Team (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria."]}

This project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Project Number 391977956, SFB 1357, subprojects B05.