Describing Patterns in Flow-Like Images

We are interested in the development of an efficient computational visual system to study dynamic fluids. So, in this paper, we present a methodology to detect patterns in flow-like images. These patterns are called, in the Dynamical Systems theory, critical points or single points. This method involves four steps: estimation of flow directions; matching; critical point confirmation, and critical points description according to the Dynamical Systems theory. At the second step, to achieve the critical point class, node, saddle or center point, we use templates to match the patterns. The last step of the method is necessary only if we wish a numerical representation of the patterns. We ran the method over several real images of some fluid flow classes and present the results.