Hashing algorithms map data to an arbitrary fixed-size value. Most hashing algorithms actively try to avoid collisions – e.g., minimizing the probability of two different keys having the same hash. Perceptual hashes do the opposite – they maximize collisions by creating some dimension of data locality – similar keys have similar hashes.