TinEye is a reverse search engine which can find related images (and other information) based on a source file:
“TinEye is a reverse image search engine. You can submit an image to TinEye to find out where it came from, how it is being used, if modified versions of the image exist, or to find higher resolution versions. TinEye is the first image search engine on the web to use image identification technology rather than keywords, metadata or watermarks. It is free to use for non-commercial searching.” [Read More]
TinEye has been developed by Idée Inc who also market a number of other related services (principally aimed at larger scale media operations or heavy image users).
A question that often comes up when people start using MD5 checksums is whether they can be used to identify resized, cropped, or otherwise modified images. A simple MD5 hash won’t detect a duplicate that has been modified (even slightly) because it is based on a fairly simplistic technique that is more commonly used for cryptography/authentication applications to verify that a file has not been tampered with. However, technologies like TinEye point the way towards more advanced DAM systems that are able to carry out a more sophisticated analysis and identify those that humans would tend to regard as duplicates (e.g. crops, colour balance changes etc).
Having played around with TinEye, I do think it looks a like this is going to become a standard feature for DAMs within the next few years (especially image or photo oriented ones) as there are numerous scenarios and practical applications for this kind of technology and it was surprisingly effective with the samples I tested.
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