algorithm - clustering a set of rectangles -


i have set of rectangles need cluster together, based on euclidean distance between them.the situation explained in attached image. the situation explained in attached image.

one possible approach take center of each rectangle , cluster center points using k means (distance function euclidean distance in xy plane). however, know if there other approach problem, not approximate rectangle it's central point, takes actual shape of rectangle consideration.

have @ algorithms such dbscan , optics can used arbitrary data types long can define distance between them (such minimum rectangle-to-rectangle distance).

k-means not good, designed point data squared euclidean distance (= sum of squares, within-cluster-variance).


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