Image recognition - that is - the automated determination of the visual contents of an image parsed into text, is the holy grail of search. Back in July, we wrote about it (Image Recognition and the Future, 7/2/08) and several very interesting advances - and for you bleeding-edge readers out there, a behind the scenes look at how.
With the speed of Moore's Law applied, fast-forward to present day, with the here-to-fore unknown "Automated Linguistic Indexing of Pictures Real Time" - or ALIPR. (note it seems to be missing a "T" in the acronym.) Now, it launched in 2006, but it's just hit my radar this weekend, thanks to the good folks at TechRadar.com (Automatic image tagging gets smarter, 10/9/08), and LifeHacker (ALIPR Learns How to Auto-Tag Photos, 10/11/08), which also has other examples.
Here's one example of a fairly successful (but by no means exhaustive) result return, where I've checked the applicable keywords (click each to see them a bit larger):
Here are several others with less than stellar results. Of particular interest is what it DID return. Stop and think about how it came to choose the keywords it did - patterns, colors, and so forth:
As this technology gets more effective, there will be an inverse law applied to the technology from a keywording perspective. Just as we are on the lookout for an amazing automated piece of software that will generate keywords for us (like this one, albeit in it's admitted infancy) so that our images can be more easily found by those needing to find them, we will not need keywording (or atleast need it less than we do now) because we will have search results that return the images we need, even without the keywording.
To give it a spin yourself, visit them here.
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