Perceptual hashing is the use of a fingerprinting algorithm that produces a snippet, hash, or fingerprint of various forms of multimedia. A perceptual hash is a type of locality-sensitive hash, which is analogous if features of the multimedia are similar. This is not to be confused with cryptographic hashing, which relies on the avalanche effect of a small change in input value creating a drastic change in output value. Perceptual hash functions are widely used in finding cases of online copyright infringement as well as in digital forensics because of the ability to have a correlation between hashes so similar data can be found (for instance with a differing watermark).
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The 1980 work of Marr and Hildreth is a seminal paper in this field.The July 2010 thesis of Christoph Zauner is a well-written introduction to the topic.In June 2016 Azadeh Amir Asgari published work on robust image hash spoofing. Asgari notes that perceptual hash function like any other algorithm is prone to errors.Researchers remarked in December 2017 that Google image search is based on a perceptual hash.In research...
Stéphane Bortzmeyer
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