Using optical flow equation for particle detection and velocity prediction in particle tracking

A new algorithm of particle identification suitable for particle tracking technique in fluid mechanics is proposed and tested with synthetic images specifically developed with different particle parameters. The new approach is based on the solution of the optical flow equation via a sum-of-squared-difference method. Particles are detected through the identification of corner features, where image intensity gradients are not null in two orthogonal directions. It is thus possible to identify low intensity and overlapped particles. Furthermore, the feature selection criterion is optimal by construction because it is based on the optical flow solution and therefore a good feature is the one that can be tracked well. This leads to the second advantage of the method, which is the possibility to obtain the local velocity, given by the approximate solution of the optical flow equation, that can be used as a predictor for the subsequent particle pairing step. The proposed algorithm is tested using synthetically generated and experimental images and demonstrates its ability to detect a great number of particles with high reliability in different cases analysed.