Helene Martin¹, Solmaz Boroomandi Barati², Jean-Charles Pinoli¹, StephaneValette² and Yann Gavet¹, ¹Ecole Nationale Superieure des Mines de Saint-Etienne, France and ²Univ Lyon, France

This study deals with developing an image processing algorithm that is able to recognize spherical and ellipsoidal droplets growing on pillared surfaces during heterogonous dropwise condensation. The problem with recognizing droplets on the pillared substrates is that droplets are very similar to the pillars or they cover several pillars at the same time, so characterizing the pillars is very important. On the other hand the droplets are not always perfectly spherical or they are connected and form irregular shapes, in such cases the ability to recognizing and separating connected droplets is another challenging step. The method that is used here consists of three main parts: pillars characterization, droplets categorizing and droplets segmentation. The result of this algorithm will be binarized images that enable to extract the information related to the size and density of droplets needed for studying droplets evolution during time. Also a computer simulation method is proposed to generate ellipsoidal droplets on pillared substrate. The results of this algorithm then are validated by comparing with results from experimental procedure.

Dropwise Condensation, Image Segmentation, Textured Surface, Droplets Recognition