William Thielicke

Dear Sina,
Images are not binarized. PIVlab however only uses intensity information from the images.
There should be minimally around 6 particle pairs in the last pass. The larger the interrogation area is, the better are the individual vectors. But you lose resolution of course.
When there are no particles in a region, then PIV doesn't work... The challenge usually is to optimally set up the experiment , but I guess thiss will be hard in your case... Please send me some images, ans I can have a look.

Dear Ian, the amount of erronoeus vectors depends on your image quality. Image noise or compression artifacts can really become a problem. You can filter erroneous vectors semi-automatically by applying e.g. the stdev filter, the normalized median test, or a global velocity threshold. You can also send me some of your images so I can have a look.

The correlation result is here:
piv_FFTmulti.m
result_conv=result_conv/max(max(result_conv))*255; %normalize, peak=always 255

Many thanks for your precious help. I will send you some of the snapshots.

Dear William,
Thank you for the amazing PIV code that you created. I am working with a series of images obtained in a dense fluidized bed made of many particles. Some questions that arose while I started working with your PIV lab are:
1. Does the program binarize all the images once I do the image pre-processing?
2. There are regions where there is no particle but I see that there are many velocity vectors that should be avoided somehow.
3. How should I choose Pass1, 2 and 3? Is there a certain criteria for that?

I'll be happy to send you some of the images too.

Best regards
Sina