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Eliminate tedious and error-prone manual counting of repetitive features in images. Take a picture of a connector, drag a line across the image to indicate "pins are here", and the computer will tell you "25 pins!". Take a picture of a building, drag a line up the side to indicate "windows are here",
and the computer will tell you "18 stories!". Take a picture of a gear, draw a circle around it, and the computer will tell you "37 teeth".
This should be trivial, and it'd be really useful. I've seen similar "measure" tools used in GIS apps, but none do "counting" of repeating image features.
How many jelly beans are in the jar?
http://chocolatecan...01/JBJellyBeans.jpg
[Klaatu, Sep 06 2006]
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//This should be trivial, and it'd be really useful.// |
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Trivial? How would it work then, and what kind of algorithm would you use for this? |
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How would you allow for reflection, colour, size, shape, boundaries etc. |
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I like the approach - it is a good idea.
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But, at the same time, I'm with webfishrune here - it really doesn't sound trivial at all. Despite recent developments in image recognition each application is really quite specialised (fingerprint, facial, ocr etc) I don't know if such a generic 'feature identifier' exists, short of a living brain.
Try convincing us, or it's got to be an mfd for magic I'm afraid. |
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To aid the computer, you might need to manually select the "ideal" feature and "the worst looking approximation that should still be counted as the feature". Then the computer can choose what resolution to study the picture in. |
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//Count pins, bricks, lines, in a digital
photo// - so what would it count if
confronted with a photograph of a wall
covered with holes, some of which were
empty, some having a spider in them,
some a fly and others bunches of spiky
hair shaved from a mob of angry
mohicans? Well ??? |
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Will wait to see quality of answer before
voting. |
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Not trivial. Computers suck at identifying "things" and even more so pictures of "things". This is absolutely trivial for a human, but still impossible for a computer. |
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Think of how hard it is for the scanner at the grocery store to just identify and read the barcodes on your groceries. I see failure rates of at least 25%. (First pass.) And that is a fixed format, two color, maximally simplified glyph. |
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Thanks [bigsleep], Interesting, but somewhat illustrates my point. |
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Identifing stuff is very difficult for computers. I notice that that article talks a lot about changes being made in the plates to make them easier for the systme to read, and changes in the camera set ups to make the images more consistant. |
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And still you are only requiring the system to identify a very small set of symbols. Letters and numbers, in high contrast. |
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Identifying arbitrary items (bricks, windows, chickens, protestors) is orders of magnitude more difficult. |
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