Many phenomena in chemical processes for example fast mixing, coalescence and break-up of bubbles and drops are not correctly described using average turbulence properties as the outcome is governed by the interaction with individual vortices. In this study, an efficient vortex-tracking algorithm has been developed to identify thousands of vortices and quantify properties of the individual vortices. The traditional algorithms identifying vortex-cores only capture a fraction of the total turbulent kinetic energy, which is often not sufficient for modeling of coalescence and break-up phenomena. In the present algorithm, turbulent vortex-cores are identified using normalized Q-criterion, and allowed to grow using morphological methods. The growth is constrained by estimating the influence from all neighboring vortices using the Biot-Sawart law. This new algorithm allows 82% of the total turbulent kinetic to be captured, at the same time the individual vortices can be tracked in time. (c) 2015 American Institute of Chemical Engineers AIChE J, 62: 1265-1277, 2016