Particle Image Velocimetry (PIV) is a method to measure space- and time-resolved flow velocities in fluids. Because no suitable software for my PhD research was available in our lab, my PhD supervisor Eize Stamhuis and me recently developed a PIV software (called PIVlab) that takes advantage of numerous MATLAB features. I also created an extensive GUI for the software which makes it easy for both beginners and experts in PIV to get accurate results.

The 'heart' of the software is the correlation algorithm. Direct cross correlation (in the spatial domain) and a discrete Fourier transform correlation (in the frequency domain) can be selected. The displacement of the particles is calculated in several passes while the grid is refined and the interrogation windows are deformed. The data can be validated, interpolated and smoothed; a lot of data extraction tools and export formats are available. Of course, derivatives like vorticity, magnitude of velocity etc. are also available.

Our open-source software is used in numerous scientific studies all around the world and it receives very positive feedback. Further details can be found on the PIVlab website.

PIVlab was selscted as 'Pick of the Week' by MATHWORKS, and was tagged as popular file 2018. It reached around 1000 scientific citations until end of 2019.

Screen capture of PIVlab:

Video of an analysis:

Tutorial video:

Analysis of a vortex ring, colored with velocity magnitude and line integral convolution: