https://github.com/j-colas/piv_demo

Simple Particle Image Velocimetry algorithm demo based on zero-mean cross correlation.
https://github.com/j-colas/piv_demo

Last synced: 23 days ago
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Simple Particle Image Velocimetry algorithm demo based on zero-mean cross correlation.

• Host: GitHub
• URL: https://github.com/j-colas/piv_demo
• Owner: j-colas
• License: gpl-3.0
• Created: 2019-05-26T18:26:16.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-05-26T19:34:14.000Z (over 5 years ago)
• Last Synced: 2024-02-16T13:31:19.450Z (9 months ago)
• Language: Python
• Size: 528 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Particle Image Velocimetry Demonstration

Simple Particle Image Velocimetry algorithm demo based on zero-mean cross correlation.

## Description 

### 1/ Images generation 

N gaussian particles are located randomly in the first frame. We applied an Affine transformation to the first frame to generate the second one. Gaussian noise is added.  

### 2/ PIV 

Frames are subdivided in smaller region of interest (ROI). We compute the zero-mean cross correlation (ZMCC) with Fast Fourier Transform on each ROI two by two (ROI_frame_1, ROI_frame_2). The displacement is estimated by finding the location of the maximum in the result of the ZMCC.

## Example of motions

We tested different motions :

#### [1] Shearing 

#### [2] Translation 

#### [3] Rotation 

![alt amplitude spectrums](https://raw.githubusercontent.com/j-colas/piv_demo/master/result_piv.png)