Fast Fourier Transform (FFT) Examples
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The following example illustrate how to use the IMAQ FFT functions for image analysis.
The first example shows how to use the FFT functions to interactively filter an image in the frequency domain. First, the Sinusoidal Image Generator VI generates an image with horizontal and vertical sinusoidal patterns. You can adjust the frequency of these patterns from the front panel.
After displaying the original image, the VI displays the FFT of the image and then prompts you to select a region of interest (ROI). If you zoom into the center of the image, or where the high frequency information resides, you will see four dots that represent the +/- vertical and horizontal frequencies. Next, the VI multiplies the mask by the image in the complex domain. The result is then converted back to the time domain using the IMAQ Inverse FFT function.
Note: To select only the horizontal components of the image, hold down the Ctrl key and select multiple ROIs. This will filter out all of the vertical components.
The second example provides an easy way to benchmark FFT algorithms. This example allows the user to specify the size of the image and the example returns how long it takes to perform the FFT.
Filename: 3600.vi
Application Software: LabVIEW Base Development System 7.1
Toolkits and Add-Ons: LabVIEW Vision Development Module 6.1
Language(s): LabVIEW
Filename: 3599.llb
Application Software: LabVIEW Professional Development System 7.0
Toolkits and Add-Ons: LabVIEW Vision Development Module 7.0
Language(s): LabVIEW
The first example shows how to use the FFT functions to interactively filter an image in the frequency domain. First, the Sinusoidal Image Generator VI generates an image with horizontal and vertical sinusoidal patterns. You can adjust the frequency of these patterns from the front panel.
After displaying the original image, the VI displays the FFT of the image and then prompts you to select a region of interest (ROI). If you zoom into the center of the image, or where the high frequency information resides, you will see four dots that represent the +/- vertical and horizontal frequencies. Next, the VI multiplies the mask by the image in the complex domain. The result is then converted back to the time domain using the IMAQ Inverse FFT function.
Note: To select only the horizontal components of the image, hold down the Ctrl key and select multiple ROIs. This will filter out all of the vertical components.
The second example provides an easy way to benchmark FFT algorithms. This example allows the user to specify the size of the image and the example returns how long it takes to perform the FFT.
| Related Links: |
| Automatic Focus Using FFT |
| Save FFT Image to file |
Requirements
Filename: 3600.vi
Software Requirements
Application Software: LabVIEW Base Development System 7.1
Toolkits and Add-Ons: LabVIEW Vision Development Module 6.1
Language(s): LabVIEW
Software Requirements
Application Software: LabVIEW Professional Development System 7.0
Toolkits and Add-Ons: LabVIEW Vision Development Module 7.0
Language(s): LabVIEW
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