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Have you ever searched for an image, found it, but the link was broken? You had no formal name for the image, the description wouldn't bring up any other links, but you had the thumbnail image with no corresponding full size image. You can usually find what you want after enough text searching and
browsing, but it'd be bitchin If you could use that thumbnail to search for the larger image. I don't know if this is technically possible, but would be useful.
CIRES
http://amazon.ece.u...~qasim/research.htm
Content-Based Image Retrieval System [jutta, Mar 31 2006]
Only if you can draw really well
cartoogle
Proof of concept [methinksnot, Apr 01 2006]
GooglePix
GooglePix_20search
[DesertFox, Apr 01 2006]
Retrievr - Flickr
http://labs.systemone.at/retrievr/
[Dub, Apr 03 2006]
[link]
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This is like the porn facial recognition search in this category, but widely applied. |
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Yeah jutta, that's good, but you can't use your provided pic to search. |
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I think that isn't the right adjective to use here. Also, your first sentence needs a question mark. |
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How is a search engine going to know what it is about that image that you are searching for? |
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Since in [miggavin]'s case we have a thumbnail that's mechanically related to the sought-after image, you don't need to answer that. |
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In the more general case, at worst, you'd perform scene analysis - simulate whatever it is a person does when you show them an image and they figure out what it "means". Not easy, not impossible, existing Computer Vision research topic. |
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[jutta] That is kind of my point. Computer vision is crap at the moment. It is supposed to get better in the next five years, and has been that way for fourty years. It is really easy for a human to tell that a picture represents a croissant on a plate rather than nude model on a bed, or a turd in a puddle, but grapically these are very similar things. |
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But, Galbinus, miggavin isn't searching for *similar* images, s/he is "bitchin after" other copies of the *same* image (for the metadata), or scaled-up versions thereof. |
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If thumbnails were all the same size, didn't undergo alternative lossy compressions, and didn't suffer from bit-rot (re-encoding with a lossy format), then it would be relatively easy. Find all images, generate their thumbnails, hash them.
But they are and do, so it is a bit more tricky. |
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Perhaps wavelet-style compression would be useful?
Divide the image into quadrants, work out the average colour for each, and store it. Iterate one or more times on the quads for increasing accuracy. This could give quite an efficient multi-levelled seaching algorithm.
It also has the advantage of coping with distorted aspect ratios, but wouldn't necessarily find cropped or colour-processed derivatives*. You may be able to deal with the latter to some extent by pre-processing to get an average colour balance, but for the former... you can't have everything. |
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*In the thumbnail case it itself would be the derivative, but I'm thinking it would be a useful plagarism-detection tool as well. |
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Thumbnail to larger version might be possible, if the algorithm for the thumbnail generation were known. But if the source image had been processed further than it would be very difficult to identify. |
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Baked - Like this? (link) |
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//If you could use that thumbnail to search for the larger image// |
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- between this comment in the original idea text and Loris' ideas it seems workable. |
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Rather than looking for an exact image match to be returned straight away, instead you'd get a set of close results back depending on the match criteria used and then the human operator could weed out from that limited set those that are out of context, such as nude models who look happen to look like croissants - you know, even when I squint I'm not seeing that one, but I've got to ask - G_C just what did make you first notice this site? ;) |
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