Image analysis for the time-resolved description of microparticle resuspension under transient airflow

This paper presents an automatic particle detection algorithm to study the time-resolved resuspension of isolated microparticle mono-layers exposed to airflow acceleration followed by steady-state. The algorithm post-processes movies of the deposit behaviour and returns the particle number, the granulometry, and the homogeneity of each frame. It allows the detection and isolation of the particle clusters to process them separately. The algorithm is validated using both synthetic images, and experimental datasets corresponding to ventilated duct cases. The number of particles remaining on the surface over time is returned, and correlations can be made with instantaneous physical parameters of the flow (e.g., centre or friction velocity). The algorithms and data are available online: see Cazes et al. (2023); CAZES et al. (2023), respectively. •Description of an automatic algorithm that detects particles in images.•Direct access to particle number and particle size distribution.•Detection of particle clusters and separation of particles therein.•Fast treatment of large image sequences.•Study of microparticle resuspension using a time-resolved approach.