LabVIEW
Image Acqusition-Line Profile and Spatial Frequency of Spectrum
Solved!
Thank you. I apologize for not taking a closer look earlier, but I've now run your VI along with the data you attached earlier, and can explain the multiple "mis-understandings" you had that resulted in incorrect code. I'll also attach the corrected code that calculates the FFT in two ways, one being the FFT you were attempting to make of the entire 2D Image (which has nothing to do with an ROI and a line profile) and the other of the correct way
This is (a slightly-modified version of) the VI you submitted, derived from the LabVIEW Vision Examples:
When you select a line ROI across the top of the "fringed" Image that you submitted (pointed to by File Path), you correctly display the Line Profile and the summary Line Information. If you look at the Line Profile, you'll see a sinusoidal intensity plot that looks rather like the fringe intensity (as it should!). But then you go astray. IMAQ FFT computes the 2D FFT of the original Image. It requires, as a second input (Image Dst) a complex Image. So here is the first "confusion" -- what does IMAQ mean by "Image"?
In one sense, an Image is a 2D array of pixels that, when viewed and displayed, form an "image" (or a picture). In IMAQ, it also can refer to a pointer where such an array of Pixels is stored in memory, or, perhaps, in the Driver for an IMAQ or IMAQdx Camera. It can also refer to the Front Panel Image Display, or to the wire (of type IMAQImage) that connects all of these things.
What IMAQ FFT requires for its Image Dst input is an Image "buffer", a place to store the resulting 2D Complex FFT this function will produce. You create this using the IMAQ Create function, being sure to specify the Complex Image type. The output, Image Dst Out, should be a Front Panel Image Display so you can look at the 2D FFT.
So what about the Line Profile you created? This is in the form of a Waveform Cluster, which you (correctly) plotted on a Waveform Graph. It is a 1D array of pixels, and can be sent to a Waveform FFT Transform to get the Amplitude spectrum.
Here is a modified and corrected version of your routine. I moved the two FFT computations outside the While loop just for neatness. You'll also notice that I used the selection of the ROI as the signal to exit the While loop (just to simplify the code a bit). You'll see the creation of the buffer to compute the 2D FFT, the Image Display (labeled FFT) to show it (the bottom indicator called FFT -- I didn't notice I named an Image and a Graph both "FFT"), while the computation of the Line Profile's FFT is shown above.
(Aha -- the Snippet named the Complex FFT Image Display "FFT 2")
Drat -- I was going to show you what the Front Panel looks like, so you can see the Line Profile with its oscillating Intensities, the Line Profile FFT with a peak at DC (because the data are not zero-meaned), another at 0.1 (full scale is 0.5, with the units needing to be converted in order to get out Frequency), a 2D FFT that is mostly black, but with a short bright vertical streak about a third of the way in from the left and centered (more-or-less) vertically (again, I don't have scaling on these plots, but you should be able to work it out).
Bottom line -- there is quite a bit of power in the NI Vision Module, but the documentation and examples don't always explain things fully. Experimentation and Experience are the best teachers.
Bob Schor
