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Id
8428923
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0
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0
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2
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CreationDate
2011-12-08T09:40:57.377
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2011-12-08T15:05:00.683
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2011-12-08T15:05:00.683
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205714
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205714
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8428865
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2
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1
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text
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If the object is reasonably rigid and aligned, simple <a href="http://www.google.hu/url?sa=t&rct=j&q=autocorrelation&source=web&cd=1&sqi=2&ved=0CBwQFjAA&url=http://en.wikipedia.org/wiki/Autocorrelation&ei=DofgTt-vAYKh4gTTn9TWBg&usg=AFQjCNF0XVfggjIk1I8jkXSXcHDSNDwGxw&cad=rja" rel="nofollow">auto-correlation</a> would do the trick. If not, I would use <a href="http://www.google.hu/url?sa=t&rct=j&q=ransac&source=web&cd=1&ved=0CB0QFjAA&url=http://en.wikipedia.org/wiki/RANSAC&ei=9obgTtLqHeyP4gTawYyTBw&usg=AFQjCNH5aqFVOBzJ7AAnXWK83fuHF4NN1Q&cad=rja" rel="nofollow">RANSAC</a> to estimate the transformation between the subject and the template (it seems that you have the feature points). Please provide some details on the problem. Edit: RANSAC (Random Sample Consensus) could be used in your case. Think about unnecessary points in your template as noise (false features detected by a feature detector) - they are the outliners. RANSAC could handle outliners, because it choose a small subset of feature points (the minimal amount that could initiate your model) randomly, initiates the model and calculates how well your model match the given data (how many other points in the template correspond to your other points). If you choose wrong subset, this value will be low and you will drop the model. If you choose right subset it will be high and you could improve your match with an LMS algorithm.
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1. This table or related slice is empty.
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1. PO2D Point Set Matching
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1. USWebMonster
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1. USWebMonster
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1. COwell, i am detecting rectangles on both: the template and the scan image. now i would like to use the edge points (blue,green,red circles) to wrap the image... i dont know any correspondence of the points, which you need for findHomography (openCV)/RANSAC?
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2. CObut i still need point pairs for the RANSAC? something to match the points of the scan and template image? http://opencv.itseez.com/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html#findhomography
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