http://imagej.273.s1.nabble.com/What-is-the-best-approach-towards-finding-a-grid-tp5010417p5010422.html
what about FFT, select the first-order maxima and fill them with 255, run Inverse FFT and "Find Maxima"?
Depending on the image data, you might want to do some preprocessing to suppress the background.
> Hi,
>
> We are analyzing images where we need to quantify the size of "white blobs"
> arranged in a grid format. The grid is organized in equal spacing in the x
> and y directions. Some blobs might be missing, and the blobs may be on a
> slightly slanted line (i.e., the grid may be rotated by up to 10-15
> degrees).
>
> My problem is to locate the grid. The simple way to do this is the
> following:
>
> for each possible Xstart
> ---for each possible Ystart
> -----for each possible angle,
> --------- sum the whiteness at each position of the grid
> At the end, keep the X/Y/angle that maximize whiteness.
>
> The problem is that the grid contains 1536 points and so each iteration
> takes a lot of time and there are ~16000 of them (40 Xstart * 40 Ystart *
> 10 angles). I was thus wondering if one could speedup the "whiteness
> measurement" by summing simultaneaously all the pixels corresponding to the
> grid position? At the moment, we have 1536 ROIs and this is way too slow.
>
> Is there a more efficient way to approach this problem?
>
> Thank you,
> Avital
>
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