lecture14

lecture14 - CAP5415 Computer Vision Spring 2003 Khurram...

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CAP5415 Computer Vision Spring 2003 Khurram Hassan-Shafique
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Region Segmentation
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Region Segmentation Find sets of pixels, such that All pixels in region i satisfy some constraint of similarity. n R R R , , , 2 1 I R i i = ± = 2200 j i R R j i ,
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K-Means Choose a fixed number of clusters Choose cluster centers and point-cluster allocations to minimize error can’t do this by search, because there are too many possible allocations. Algorithm fix cluster centers; allocate points to closest cluster fix allocation; compute best cluster centers x could be any set of features for which we can compute a distance (careful about scaling) x j - μ i 2 j elements of i'th cluster ± ² ³ ´ µ i clusters &
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K-Means
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Image Segmentation by K-Means Select a value of K Select a feature vector for every pixel (color, texture, position, or combination of these etc.) Define a similarity measure between feature vectors (Usually Euclidean Distance). Apply K-Means Algorithm.
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lecture14 - CAP5415 Computer Vision Spring 2003 Khurram...

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