Cool idea in theory, but in practice you shift the cognitive load to the pattern recognition capabilities of the user, which might be even worse. The example fi

Cool idea in theory, but in practice you shift the cognitive load to the pattern recognition capabilities of the user, which might be even worse. The example fingerprints differ in just a couple cells, out of 48! What's worse, the general "shape" induced by the pattern is the same, they only differ in subtle details that cover small total area without changing the overall shape. The visualization you provide is more appropriate for machine recognition, but for a human the difference is so subtle that the fingerprints are genuinely hard to tell apart. Making a mistake while distracted or tired will land you into a wrong bus. You may want to dive into the cognitive science to construct a better visualization that relies on actual visual capabilities of humans, rather than on math. Start with the provable fundamentals of human perception, and answer the question - what exactly maximizes the visual difference between patterns? What exactly makes them obviously, strikingly different at the first glance? Color and value contrast, shapes, real life object resemblance, optical illusions, etc. This will also make the idea intuitively apparent to the user, without having to explain it. Be aware that these questions are not easy to answer; it's a rabbit hole which goes down to the Earth core. Visual complexity is also a thing, and bandwidth as well. You can only fit so much bits of information into the pattern, even if your mapping between the underlying logic and the presentation fits human perception perfectly.