Perceptual hashing
Perceptual hashing is the use of an fingerprinting algorithm that produces a snippet 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). Based on research at Northumbria University, it can also be applied to simultaneously identify similar contents for video copy detection and detect malicious manipulations for video authentication. The system proposed performs better than current video hashing techniques in terms of both identification and authentication.

In addition to its uses in digital forensics, research has shown that perceptual hashing can be applied to a wide variety of situations. Similar to comparing images for copyright infringement, a group of researchers found that it could be used to compare and match images in a database. Their proposed algorithm proved to be not only effective, but more efficient than the standard means of database image searching. In addition, a team from China discovered that applying perceptual hashing to speech encryption proved to be effective. They were able to create a system in which the encryption was not only more accurate, but more compact as well.

See also
 Geometric hashing
 Reverse image search
 Digital video fingerprinting

References

External links
 pHash - an open source perceptual hash library
 Blockhash.io - an open standard for perceptual hashes (GitHub)
 Insight - a perceptual hash tutorial
 pHash Coding - Perceptual Hash Related Open Source Projects

Hashing