Pattern recognition using 2D fft in matlab I have a dataset with two columns (width and length, both in milimeter). When I make a scatter plot (please refer to the first figure), I see location of defects in a plane. I want to find if the location of the defect has some kind of pattern or it is just a noise. For that I was suggested to use 2D fft to recognize pattern. I don't have any background in 2D fft but I read some articles and used matlab function fft2. I get a plot (please refer to the second figure) which I dont I understand so much at this moment. Can any one has hint to get me going? A nice article could also be of help. I read the following article as well. 

http://www.qsimaging.com/ccd_noise_interpret_ffts.html

Thanks in advance!
DFT is a great tool to find periodic patterns in signals.  However, you should understand what kind of period you want to find. If you want to find a series of points that lie on a regular grid (with even spacing), or more mathematically speaking, a subset of points $(x_i,y_i)$, such that there exists $(dx,dy)$ for which the following equations hold: 

$x_i = x_1 + dx*i $
   $ y_i =y_1 + dy*j $ 

(The patterns can also be rotated, and DFT will still find them). 

You should compute a 2D histogram of your data, with large number of bins, and run DFT on it. Afterwards, you should look for a peak in any location expect the DC. An ideal noise should have no patters, thus the contrast of the frequencies responses should be very low.