The simplest approach is to check every single point. Compute the distance from the user's location to every restaurant in the database, keep the ones that are close enough, and throw away the rest.
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confusable-vision takes the 1,418 TR39 confusable pairs that map a non-Latin character to a Latin target (a-z, 0-9), renders both characters across every available system font, and computes SSIM for each pairing. The output is a scored JSON artifact: one continuous similarity score per pair, per font.