In a sufficiently large random image, you'll (probably) find as detailed of a picture of a rabbit as you like. The question is about how often image recognitio

In a sufficiently large random image, you'll (probably) find as detailed of a picture of a rabbit as you like. The question is about how often image recognition (either human or algorithmic) picks up a signal in random noise -- that is, how often we see things that aren't there (or if you prefer, are there, but by chance). Of course you can find anything, the question is with what frequency. If you've ever spent much time looking at random patterns, you'd know that we're prone to seeing things that aren't there in noise. Modeling that phenomenon is interesting (at least to me).