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The scheme was published by Andrei Broder in a 1997 conference, [1] and initially used in the AltaVista search engine to detect duplicate web pages and eliminate them from search results. [2] It has also been applied in large-scale clustering problems, such as clustering documents by the similarity of their sets of words. [1]
Find duplicates, hierarchical keywords, distributable catalog with free Media Pro reader, offline browsing of images Picasa: Yes name, date, rating, faces Yes individual, linear Partial Keywords Partial basic Yes Yes Yes rotation only Yes collages, Geotagging, Search for Faces, find duplicates Shotwell: No Yes individual, linear, hide Yes
A large scale evaluation has been conducted by Google in 2006 [2] to compare the performance of Minhash and Simhash [3] algorithms. In 2007 Google reported using Simhash for duplicate detection for web crawling [4] and using Minhash and LSH for Google News personalization.
An image search engine is a search engine that is designed to find an image. The search can be based on keywords, a picture, or a web link to a picture. The results depend on the search criterion, such as metadata, distribution of color, shape, etc., and the search technique which the browser uses.
Not specific to pictures, but I've found Duplicate Cleaner works well at finding duplicates. TastyCakes 15:16, 26 November 2009 (UTC) Visipics and DupDetector are two freeware programs for finding duplicate images. They can find similar pictures of different sizes.
Fuzzy hashing exists to solve this problem of detecting data that is similar, but not exactly the same, as other data. Fuzzy hashing algorithms specifically use algorithms in which two similar inputs will generate two similar hash values. This property is the exact opposite of the avalanche effect desired in cryptographic hash functions.
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