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I had a similar problem, but with a QVGA-sized matrix and not just a small array like this guy.

I used some Numerical Recipes formulas to do a linear interpolation on the data and upscale it into a larger grid, then used OpenCV to threshold and then find contours.

It works pretty well, but I wish I could process the data faster. I fear using this Python example with mapping and overlaps would just run way way longer.




I'm pretty sure you can compute a contour from the raw data much more efficiently.


The problem is that I'm working with a sensor set that's way smaller, like 100x smaller. The peaks can be somewhere in the middle and the only way to locate those is by running an Nth order interpolation (or maybe doing something simpler like computing local averages)




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