Image analysis technique has been proved to be very effective in the quantification of particles size and morphology distributions in different work areas. In the present research topic, this technique has been combined with the discriminant factorial analysis (DFA) in order to allow the automatic identification of polymorphic, agglomerates, droops, bubbles, etc, in multiphase systems (Figure 1.). With the previous methodology, it has been possible to distinguish online and automatically among five different classes of particles, bubbles or droops, allowing the computation of the particles, bubbles or droops complexity in the system (Figure 2.).
Figure 1. Sequence of operations performed on the images before numerical descriptors extraction.
As example, this automatic classification allows better quantification of bubble sizes in a bubble column (BC) bioreactor, and as this classification is based on several probabilities of each bubble belonging to each group considered, it has also been possible to obtain the complexity or turbulence of the system based on the degree of bubble complexity (BCD) (Figure 3.). This information is very useful to understand the bubble size distribution and the mass transfer process in a BC concerning the influence of other bubbles on the concentration profiles surrounding individual bubbles.
Figure 2. Image analysis software
Figure 3. Bubble size distribution and classification: bubble complexity degree (BCD).