Performance Evaluation of the PMC and the KC Methods for Particle Extraction and Tracking through Their Application to Standard Particle Images

Abstract

The PMC method, the particle mask correlation method, was presented to pick up particle images. The KC method, a combinative use of Kalman's filtering theory and the Chi-square test, was developed for particle tracking velocimetry. A set standard particle images in fluid velocity fields were generated to evaluate performance of PTV algorithms. The PMC and the KC methods are applied to the standard particle images, which proved higher performance of these methods than other existing PTV algorithms with respect to resolution of resulting velocity fields.